50+ Python Jobs in India

Lead SDET/QA Test Automation Engineer – AI Platforms (Agentic AI)

📍 Hyderabad, India | Full-Time | On-site / Hybrid

📈 Experience: 6–10 Years

The Role

We're looking for a hands-on Lead SDET to define and scale quality engineering across our healthcare AI platform.

This is an 80% IC and 20% leadership role, focused on building next-generation testing infrastructure, establishing quality standards, and mentoring engineers.

What You'll Do

Quality Architecture

• Define company-wide quality strategy.
• Architect automation frameworks from the ground up.
• Establish testing standards and engineering practices.

AI Systems Testing

Own validation strategies for:

• LLM Applications
• Voice AI Platforms
• Conversational AI
• Agentic Systems
• Multimodal AI

Build frameworks for:

• Hallucination testing
• Safety testing
• Regression detection
• AI performance measurement

Automation Engineering

Drive testing across:

• APIs
• Databases
• Web Applications
• Mobile Applications
• Distributed Systems
• Performance Engineering

Leadership

• Mentor and guide engineers.
• Drive engineering excellence.
• Influence release and architecture decisions.

What We're Looking For

• 6–10 years in SDET or QA Automation.
• Strong product engineering background.
• Expert-level coding in Python and Java.
• Deep expertise in:
• Selenium
• Playwright
• Appium
• PyTest
• TestNG
• REST Assured
• Strong understanding of:
• Distributed Systems
• System Design
• CI/CD
• SDLC
• STLC
• Experience building automation frameworks from scratch.
• Strong mentoring and technical leadership skills.

Why Join Us?

• Own quality engineering for category-defining AI products.
• Influence engineering strategy and architecture.
• Work on cutting-edge healthcare AI systems.

Senior DevOps Engineer

Location: India, Remote

Type: Contract

Department: Engineering

About Us

OpenAssets is building open standards for the next generation of capital markets, providing the trusted foundation for real-world asset tokenization and digital currencies.

We specialize in alternative asset digitization, offering regulatory-conscious tools to design, issue, and manage digital assets in complex financial environments. We also develop loyalty solutions that turn customer engagement into programmable digital assets, helping brands create personalized experiences that drive growth.

OpenAssets operates at the intersection of finance, technology, and regulation focused on building secure, scalable, and open infrastructure for the future of digital markets. Join OpenAssets and be part of shaping the future of digital finance!

Overview

We are seeking a Senior DevOps Engineer to lead the evolution of our cloud infrastructure and deployment ecosystems.

This role acts as the foundation of our engineering reliability, bridging the gap between high-performance blockchain development and robust, secure cloud operations. You will be responsible for architecting scalable AWS environments, automating mission-critical CI/CD pipelines, and ensuring the absolute integrity of our security and observability frameworks.

What You’ll Do

Cloud Infrastructure & Architecture

• Design, provision, and maintain OpenAssets’ AWS infrastructure: including EC2, ECS/Fargate, Lambda, S3, RDS, VPC, IAM, CloudFront, SQS, ElastiCache, and CloudWatch.
• Architect for high availability, fault tolerance, and cost efficiency across production and non-production environments.
• Manage networking, security groups, subnets, load balancers, and access controls to ensure a secure and well-segmented cloud environment.
• Scale infrastructure dynamically to handle platform growth, partner onboarding, and peak load events.
• Deploy, configure, and manage blockchain node infrastructure supporting on-chain integrations and smart contract interactions.

CI/CD & Automation

• Implement and maintain CI/CD pipelines using GitHub Actions and/or AWS CodeBuild for frontend, backend, and smart contract deployments.
• Manage infrastructure as code using Terraform (or OpenTofu) and/or CloudFormation to ensure reproducible, auditable environments.
• Automate build, test, and deployment processes to minimize manual effort and reduce release risk.
• Develop and maintain automation scripts in Python and Bash for operational and provisioning workflows.
• Administer and scale Kubernetes clusters (EKS) for deploying services and blockchain node infrastructure.

Security & Compliance

• Implement and enforce security best practices across infrastructure: TLS, VPNs, IAM roles, private key management, secrets management, and patch management.
• Work with the CISO to conduct infrastructure security audits and maintain compliance with data handling, uptime, and audit logging requirements.
• Manage secrets and environment configuration securely using AWS Secrets Manager or HashiCorp Vault.
• Ensure encryption at rest and in transit across all critical data stores and communication channels.
• Apply knowledge of blockchain security, including consensus mechanisms, smart contract interactions, and Layer 2 infrastructure, to harden on-chain components.

Observability & Incident Response

• Set up and maintain monitoring, alerting, and dashboards for key platform metrics using CloudWatch, Prometheus, Grafana, or equivalent.
• Establish structured logging and distributed tracing practices (OpenTelemetry or similar) across services.
• Lead incident response for production issues, triaging, communicating, resolving, and writing blameless postmortems.
• Design, implement, and regularly test backup and disaster recovery strategies to minimize data loss and downtime.

Collaboration & Enablement

• Support engineering teams in troubleshooting environment-specific issues across development, staging, and production.
• Document infrastructure architecture, runbooks, and operational procedures — keeping them current and actionable.
• Train developers on deployment tooling, CI/CD workflows, and on-call processes.
• Evaluate and introduce new tooling and practices to improve DevOps maturity across the organization.

Qualifications & Experience

• 5+ years of experience in DevOps, SRE, or cloud infrastructure engineering.
• Deep hands-on expertise with AWS: EC2, ECS/Fargate, Lambda, RDS, S3, VPC, IAM, CloudWatch, SQS, CloudFront, and ElastiCache.
• Strong experience with infrastructure as code using Terraform, OpenTofu, and/or CloudFormation.
• Proficiency with containerization and orchestration (Docker, Kubernetes / EKS).
• Experience designing and maintaining CI/CD pipelines using GitHub Actions, AWS CodeBuild, GitLab CI, or similar.
• Solid Linux systems administration and scripting skills (Bash, Python).
• Strong understanding of cloud networking and security: TLS, VPCs, security groups, IAM, private key management, secrets management.
• Experience with monitoring and observability tooling: CloudWatch, Prometheus, Grafana, ELK stack, or equivalent.
• Familiarity with distributed tracing (OpenTelemetry, Jaeger, or similar).
• Working knowledge of blockchain technologies: consensus mechanisms, smart contract infrastructure, or Layer 2 scaling solutions.
• Calm, systematic problem-solving approach to production incidents and outages.
• Strong communication skills, able to explain infrastructure concerns clearly to both technical and non-technical stakeholders.
• Fluid in English

Nice to Have

• AWS certifications (Solutions Architect, DevOps Engineer Professional, or equivalent).
• Experience deploying and operating blockchain node infrastructure (Ethereum, Polygon, or similar).
• Background in fintech, capital markets, payments, or regulated infrastructure environments.
• Experience with security frameworks and compliance standards (SOC 2, ISO 27001).
• Multi-tenant SaaS infrastructure experience.
• Experience with event-driven architectures (Kafka, SQS, BullMQ).
• Cost optimization practices: reserved instances, Savings Plans, right-sizing.
• Infrastructure as code with Pulumi or CDK.
• Open-source contributions or technical writing.

We are committed to providing equal opportunity for qualified applicants to contract positions, regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status. This is a contract opportunity, not a direct employment role.

Job Title : Agentic AI Architect

Experience : 5+ Years

Location : Hyderabad (Work From Office)

Employment Type : Contract to Hire

Job Summary :

We are seeking an experienced Agentic AI Architect to design, develop, and deploy enterprise-grade AI solutions.

The ideal candidate should have hands-on expertise in Generative AI, Agentic AI, Large Language Models (LLMs), and modern AI frameworks, with a strong focus on building scalable and production-ready AI applications.

Mandatory Skills :

Generative AI, Agentic AI, Python, LLMs, RAG, Prompt Engineering, LangChain, LlamaIndex, OpenAI, Hugging Face, AWS/Azure/GCP, MLOps/LLMOps, APIs, Microservices.

Key Responsibilities :

• Design and architect scalable enterprise AI solutions using Agentic AI and Generative AI technologies.
• Develop AI applications leveraging Python, LLMs, Retrieval-Augmented Generation (RAG), and Prompt Engineering.
• Build and orchestrate AI agents using frameworks such as LangChain, LlamaIndex, OpenAI, Hugging Face, or similar.
• Integrate AI models with enterprise applications using APIs and microservices.
• Deploy, monitor, and optimize AI applications using MLOps/LLMOps best practices.
• Collaborate with cross-functional teams to deliver secure, scalable, and high-performance AI solutions on cloud platforms.

Required Skills :

• 5+ years of experience in AI/ML, software engineering, or enterprise AI solution development.
• Strong hands-on experience with Generative AI, Agentic AI, and Large Language Models (LLMs).
• Proficiency in Python for developing AI-powered applications and intelligent agents.
• Experience implementing Retrieval-Augmented Generation (RAG) pipelines and Prompt Engineering techniques.
• Hands-on expertise with AI frameworks such as LangChain, LlamaIndex, OpenAI, Hugging Face, or equivalent.
• Experience designing and integrating REST APIs and microservices-based architectures.
• Good knowledge of cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
• Experience with MLOps/LLMOps tools for model deployment, monitoring, and lifecycle management.
• Strong understanding of scalable, secure, and production-ready AI solution architecture.
• Excellent analytical, problem-solving, and communication skills.

Preferred Skills :

• Experience with vector databases and AI orchestration frameworks.
• Familiarity with Docker, Kubernetes, and CI/CD pipelines.
• Knowledge of cloud-native architecture and distributed systems.
• Experience working on enterprise AI transformation projects.

Experience: 8+ years, senior candidates only | Type: Full-time | Location: Remote (India)

 ---

 WHAT WE'RE BUILDING

 See http://www.juliet.space

 We're building Juliet, an AI that runs marketing end to end. Our users are marketers, founders, CEOs, growth leads, agencies, and SMBs — not developers. They

 tell Juliet the goal. She plans, writes production code, and ships real marketing: conversion-optimized websites, launch assets, campaigns, audits, autonomously.

 That's the engineering problem in one line: the humans in the loop can't read code, so the agent has to get it right on her own — plan, build, self-correct,

 recover, ship.

 Under the hood: a browser-based studio backed by cloud sandboxes, a real-time SSE streaming pipeline, and a LangGraph agent working across 83 tools and 63 skill

 modules. The agent isn't bolted onto the product. She is the product.

 Small team, big ambitions. You'll ship things users touch daily, not write tickets about them.

 ---

 THE ROLE

 We're hiring one architect-level backend engineer to own Juliet's agentic infrastructure end to end. That means the agent graph, the execution environment, the

 streaming pipeline, the state and memory systems — and setting technical direction for the engineers working alongside you.

 This is a player-coach seat. You'll still write code every day, and your architectural calls become the product. You'll work directly with the founder. No PMs in

 between.

 Frontend is part of the system. You won't be leading it, but you'll need to understand how the agent's output reaches the browser and be able to ship full-stack

 features when needed.

 ---

 THE STACK

 AI agent (primary): Python 3.11, LangGraph 1.x + LangChain, Anthropic / Google / OpenAI model providers

 API (primary): NestJS 11, Supabase, Redis, PostgreSQL, Server-Sent Events

 Infra (primary): Modal cloud sandboxes, Docker, Netlify deployments

 Frontend (secondary): Next.js 15, React 19, TypeScript, Zustand, CodeMirror 6, XTerm.js

 Monorepo: Turborepo, pnpm

 ---

 WHAT YOU'LL WORK ON

 The majority of your time is here:

 Agentic AI workflows — Design, extend, and harden the LangGraph agent graph: multi-step planning, code generation, tool dispatch, self-correction, and recovery

 across 83 tools and 63 skill modules. This is the core of the product.

 Real-time streaming architecture — The SSE pipeline that carries every agent action from the Python backend through NestJS to the browser: event framing,

 reconnection, health monitoring, interrupt handling for plan approvals and clarifying questions.

 Agent execution environments — Sandbox lifecycle on Modal: container spin-up, file sync, terminal I/O, command execution, and live preview with per-asset esbuild

 bundling. The agent lives here.

 State and memory systems — LangGraph Postgres checkpointers, middleware-injected context (goals, design docs, memory anchors), conversation summarization. How

 the agent knows what it knows.

 Backend API and data layer — NestJS services, Supabase schema, Redis caching, quota enforcement, webhook handling. The plumbing the agent depends on.

 Marketing intelligence pipelines — AEO, CRO, and brand-perception audit engines: multi-LLM probing, parallel inference, streamed structured reports, result

 caching. Audit-at-scale infrastructure.

 The remaining ~25% of your time:

 Full-stack product features — Collaboration (roles and permissions), the Netlify deployment pipeline, subscription and quota flows, onboarding. You'll ship these

 end to end — backend first, frontend to close the loop.

 ---

 WHAT WE'RE LOOKING FOR

 Must-have:

 - 8+ years of professional software engineering, including meaningful time as a tech lead or systems architect who owned something end to end. Closer to ten is

 the norm for people who thrive here.

 - Both worlds on your resume: engineering rigor inside a large company and 0-to-1 ownership at an early-stage startup.

 - Production agentic systems experience. You've built and operated LLM agent systems in production with LangGraph, LangChain, or equivalent — agent graphs, tool

 use, state management, prompt engineering, evals. This means well beyond calling a chat endpoint.

 - Strong Python. You design and ship production Python daily. The agent codebase is yours to own.

 - Architect-level system design. You can own how data flows across four services, make tradeoffs under uncertainty, and defend every call.

 - AI-native development workflow. You drive Claude Code, Codex, or similar agentic tools as everyday instruments — not occasionally. You have opinions about

 working with coding agents because you do it constantly.

 - Real-time backend systems. You've built SSE, WebSocket, or streaming API infrastructure in production — not just consumed it.

 - Strong TypeScript. The API layer and most product features are in TypeScript. You're productive in it.

 Strong plus:

 - Background in developer tools, IDEs, or coding/execution platforms

 - Container runtimes and sandboxed execution (Modal, E2B, Firecracker, or similar)

 - Depth in PostgreSQL, Redis, and Supabase

 - LLM observability and evals tooling (LangSmith or similar)

 - NestJS or equivalent Node.js API framework experience

 - React/Next.js — enough to ship a full-stack feature without handoff

 - Exposure to marketing, growth, or publisher-facing products

 ---

 WHY THIS ROLE IS DIFFERENT

 You own the architecture. Not a feature factory. Not someone else's design doc. The technical execution of an AI product is yours to lead.

 The agent is the product. You're not adding AI to an existing system. You're building and operating the system that is the AI. Every architectural decision

 touches what Juliet can and can't do.

 Hard problems, always. The system spans cloud sandboxes, streaming infrastructure, multi-step agent graphs, and a full-stack web product — for non-technical

 users who can't course-correct a broken output. The bar is high.

 Small team, real leverage. Your code ships to users the same week. No layers of approval.

 ---

 HOW TO APPLY

 Send us:

 1. A short note on the most complex agentic system you've shipped: what broke, and what you'd redo. A link to something you've built that involves agent graphs, tool use, or autonomous multi-step execution

 2. What is one thing you would improve about Juliet? It could be a feature or a bug.

Job Summary

We are looking for an experienced AI Data Architect to design and build an enterprise AI-ready data platform that serves as the single source of truth for AI applications, including RAG, Agentic AI, Conversational AI, ML models, and analytics.

Key Responsibilities

• Design enterprise AI data platform and Lakehouse architecture.
• Build batch & real-time data pipelines.
• Develop semantic models, knowledge graphs, and vector databases.
• Architect RAG and LLMOps infrastructure.
• Implement data governance, security, and AI observability.
• Modernize legacy data platforms to cloud-native architectures.

Required Skills

• Python, SQL, PySpark
• Databricks, Delta Lake, Snowflake
• Kafka, Spark Structured Streaming
• AWS / Azure
• LangChain, LlamaIndex
• OpenAI, Claude, Bedrock
• Pinecone, FAISS, ChromaDB, Neo4j
• MLflow, Docker, Kubernetes, Terraform
• FastAPI, GitHub Actions, Jenkins
• Data Governance, RBAC, CI/CD

Requirements

• 12+ years in Data Engineering/Data Architecture.
• Experience with AI/ML, RAG, LLMOps, and enterprise AI platforms.
• Strong expertise in Lakehouse, Data Mesh, Cloud, and Vector Databases.
• Hands-on experience with enterprise-scale AI data architecture and governance. 

About the Role

We're looking for a Senior AI/ML Engineer who thrives at the intersection of research and production — someone who doesn't just build models, but ships systems that scale. You'll own the full ML lifecycle: architecting robust data pipelines, training and rigorously evaluating models, and deploying them into high-throughput production environments. This is a role for engineers who want their work to move fast, break assumptions (not systems), and directly shape how AI gets built at scale. If you're energized by turning cutting-edge research into real-world impact, this is your next challenge.

Key Responsibilities

– Design, build, and maintain end-to-end ML pipelines — from raw data ingestion to model serving — with a focus on scalability and reliability.

– Develop, train, and rigorously evaluate ML/DL models using sound experimentation practices (A/B testing, offline/online metrics, statistical validation).

– Own the MLOps lifecycle: implement CI/CD pipelines for model training and deployment, version control for datasets and models, and automated retraining workflows.

– Deploy and monitor models in production using containerized, orchestrated infrastructure (Docker, Kubernetes), ensuring low-latency, high-availability inference.

– Collaborate cross-functionally with Data Engineering, Product, and Backend teams to translate business problems into scalable ML solutions.

– Optimize model performance for cost, latency, and accuracy trade-offs across cloud-based training and inference environments.

– Mentor and guide junior engineers and data scientists — conducting code reviews, sharing best practices, and raising the technical bar of the team.

– Stay current with emerging research (LLMs, generative AI, RAG architectures) and proactively identify opportunities to apply them to existing products.

Required Technical Skills

Languages

– Expert-level Python; working knowledge of R or C++ is a plus.

Frameworks

– TensorFlow, PyTorch, Scikit-Learn, Keras.

Data & Cloud

– Strong SQL and NoSQL fundamentals.

– Hands-on experience with at least one major cloud platform (AWS, GCP, or Azure), specifically their ML tooling — SageMaker, Vertex AI, or equivalent.

– Experience with distributed data processing frameworks: Spark, Hadoop.

MLOps & Deployment

– Proficiency with Docker and Kubernetes for containerized deployment.

– Experience building CI/CD pipelines for ML workflows.

– Familiarity with experiment tracking and pipeline orchestration tools like MLflow or Kubeflow.

Advanced / Nice-to-Have

– Practical experience with LLMs, prompt engineering, and Retrieval-Augmented Generation (RAG) architectures.

– Experience fine-tuning transformer-based models for domain-specific use cases.

Qualifications & Experience

– Bachelor's, Master's, or Ph.D. in Computer Science, Data Science, Artificial Intelligence, or a related quantitative field.

– 5+ years of hands-on experience building, training, and deploying production-grade AI/ML models at scale.

– Demonstrated track record of taking models from prototype to production in a real-world business setting.

What We Offer

– Competitive compensation, benchmarked to top-tier tech talent in the industry.

– Comprehensive health insurance coverage for you and your family.

– Annual learning & development stipend for courses, certifications, and conferences.

– A collaborative, high-ownership culture where engineering excellence is celebrated.

– The opportunity to work on cutting-edge AI systems with direct, visible impact.

About Tech Transient

Tech Transient is an AI consulting and digital transformation firm headquartered in Coimbatore, Tamil Nadu.

We partner with enterprises and growth-stage companies to design and deliver intelligent digital products — spanning mobile applications, cloud platforms, and AI-driven solutions. Our mission is to translate emerging technology into measurable business outcomes.

Machine Learning Engineer (For client company)

Location: Bengaluru, India (Hybrid/Onsite)

Experience: 3–4 years

The Role

We are looking for a Machine Learning Engineer to build and productionize models that power fall detection, vitals monitoring, and predictive health insights from radar sensor data.

You will work closely with hardware, data engineering, backend, and product teams to improve model accuracy, reduce false alarms, and deploy reliable ML systems into production.

This role is ideal for someone with strong classical machine learning fundamentals who is comfortable working with messy real-world sensor data and writing clean, production-grade code.

What You'll Do

• Build and optimize classical ML models such as XGBoost, ensemble models, anomaly detection, and time-series models for fall detection, vitals monitoring, and health risk scoring.
• Engineer features from raw, sparse, and noisy radar signals, point-cloud data, and time-series sensor streams.
• Contribute to computer vision-adjacent problems such as pose estimation, movement analysis, skeleton tracking, and activity recognition using radar data.
• Build training, evaluation, and inference pipelines using Databricks.
• Perform exploratory data analysis on resident, device, alert, and facility-level datasets to identify trends, edge cases, and opportunities for model improvement.
• Define and own model evaluation metrics for safety-critical systems, including:
• Precision
• Recall
• Sensitivity
• Specificity
• False alarm rate
• Missed event rate
• Detection latency
• Analyze production model performance across facilities, residents, devices, and time periods.
• Handle noisy real-world datasets, including:
• Missing values
• Label quality issues
• Device variability
• Sparse event data
• Facility-specific patterns
• Write clean, modular, well-tested Python code for feature engineering, model training, evaluation, and inference.
• Deploy, monitor, and continuously improve production ML models.
• Collaborate with hardware and data engineering teams to improve data quality, labeling, observability, and model reliability.

What We're Looking For

• 3–4 years of experience building and deploying machine learning systems in production.
• Strong Python programming skills with the ability to write maintainable, testable, production-grade code.
• Strong understanding of classical machine learning concepts, including:
• Feature engineering
• Model training
• Cross-validation
• Error analysis
• Model evaluation
• Hands-on experience with algorithms such as:
• XGBoost
• Random Forests
• Gradient Boosting
• Ensemble methods
• Anomaly Detection
• Time-series models
• Strong SQL skills with experience analyzing large datasets using SQL, PySpark, Pandas, or Databricks.
• Experience working with time-series, sensor, spatial, point-cloud, IoT, or computer vision-style datasets.
• Familiarity with modern data engineering workflows using Databricks, Apache Spark, Delta Lake, or similar platforms.
• Strong debugging and analytical skills with the ability to diagnose issues across data pipelines, models, and production systems.
• Comfortable working in a fast-moving startup environment with ambiguity.
• Strong ownership mindset with the ability to take ML models from experimentation through production deployment.

Good to Have

• Experience in HealthTech, IoT, radar sensing, wearables, ambient monitoring, or safety-critical systems.

Exposure to:

• Computer Vision
• Pose Estimation
• Skeleton Tracking
• Object Tracking
• Spatial Data Processing
• Experience with:
• MLflow
• Model Registry
• Feature Stores
• Experiment Tracking
• Model Monitoring
• Experience with:
• ONNX
• Model Quantization
• Edge Deployment
• Latency Optimization
• Resource-Constrained Inference
• Familiarity with real-time data pipelines using:
• Kafka
• Spark Structured Streaming
• Streaming inference architectures 

5 -10 years of professional software development experience.

 Experience in any backend tech like Java/Golang/Python/Nodejs/Ruby and Frontend Tech like Reactjs/Angular/Vuejs

with strong working knowledge of frontend/backend frameworks.

 Strong understanding of software architecture, design patterns, and principles

(e.g., SOLID, microservices, event-driven architectures)

 Experience with AI tools, frameworks, platforms, and their application in software delivery

 Experience with cloud platforms (especially AWS services), containerization and orchestration (Docker, Kubernetes)

 Hands-on experience with CI/CD pipelines and automated testing frameworks

 Familiarity with databases (SQL and NoSQL) and data modelling

 Fluency with XP practices: TDD, pair programming, continuous integration,

refactoring

 Working knowledge of security principles (secrets management, least privilege)

vishwa.ai is an Enterprise AI-native SaaS platform built for finance, corporate lending, and risk analytics.

Our platform combines AI, data extraction, workflow automation, and analytics to help financial teams process documents, analyze businesses, assess risk, and make faster, more reliable decisions.

We are looking for a Engineer who does not just write code, but owns problems end-to-end.

This role is for someone who wants to understand the problem deeply, build the solution across the stack, work with different teams when needed, and stay accountable until the feature is actually useful for the customer.

You will not be expected to only own a frontend screen, a backend API, or a database change. You will be expected to own the problem statement.

To apply, please fill out this form: https://forms.gle/8fNfKiy3pcjYbSED9  

NOTE: Applications submitted only through Cutshort will not be considered. Please fill out the form above to complete your application.

About the Role

As an engineer, you will work across product, frontend, backend, data, infrastructure, customer workflows, and internal tools.

You should be comfortable wearing multiple hats. Some days you may be writing APIs, some days you may be debugging a production issue, some days you may be improving a product flow, and some days you may be working with stakeholders to understand what actually needs to be built.

The expectation is simple: understand the problem, figure out the right solution, build it, ship it, and make sure it works.

What You’ll Work On

Your work will include:

• Building full-stack features from scratch
• Improving existing product flows and customer workflows
• Writing backend APIs and frontend interfaces
• Working with databases and data-heavy product logic
• Debugging issues across frontend, backend, infrastructure, and data layers
• Understanding user problems and translating them into product improvements
• Working with operations, design, business, and customer-facing teams when needed
• Using AI tools to move faster and improve output
• Taking ownership of features until they are live, stable, and useful

What We’re Looking For

We’re looking for someone who can think clearly, build fast, and take responsibility for outcomes.

You should be comfortable with:

• Frontend development using React, Next.js, or similar frameworks
• Backend development using Go, Python, FastAPI, Node.js, or similar
• SQL databases, preferably PostgreSQL
• Understanding existing codebases and contributing quickly
• Debugging issues across the full stack
• Working with ambiguity and making reasonable trade-offs
• Collaborating with cross-functional teams to understand requirements
• Using AI tools as part of your daily engineering workflow
• Owning delivery beyond just writing code

You do not need to know everything already. But you should be able to learn fast, figure things out, and keep moving.

How We Work

We care deeply about ownership, trust, and quality of execution.

 Use any AI tool that helps you ship better work faster. What matters is the quality, reliability, and usefulness of what you deliver.

We value people who can take a problem, understand the business context, make technical decisions, build the solution, and drive it to completion.

You’ll Do Well Here If

• You like owning problems, not just tasks
• You enjoy building things end-to-end
• You are comfortable wearing multiple hats
• You are self-driven and can work well in a fast-paced environment.
• You can work with ambiguity and still make progress
• You care about the customer problem, not just the code
• You can make practical trade-offs between speed, quality, and scope
• You use AI tools to improve your output and speed
• You can be trusted to take a feature from idea to production
• You want to grow by taking on real responsibility

Location

We prefer someone based in Hyderabad or someone willing to relocate to Hyderabad.

That said, this is not a hard requirement. We are open to remote candidates if they are strong, reliable, and can work with high ownership.

Role

Full-time Engineer.

If you like ownership, product thinking, engineering, and solving real business problems, we’d like to talk.

To apply, please fill out this form: https://forms.gle/8fNfKiy3pcjYbSED9  

NOTE: Applications submitted only through Cutshort will not be considered. Please fill out the form above to complete your application.

Job Summary:

We are seeking a highly skilled Principal Infrastructure Engineer to join our team, focusing on production support and Site Reliability Engineering (SRE) implementation. The ideal candidate will possess a strong background in Python scripting, Ansible automation, and OpenShift support, along with expertise in Linux administration and Apache Tomcat. This role is critical in ensuring the stability and performance of our applications through effective monitoring, log analysis, and the use of various DevOps tools.

Responsibilities:

Provide production support for applications, ensuring high availability and performance.

Implement Site Reliability Engineering (SRE) practices to enhance system reliability.

Develop and maintain Python scripts for automation and process improvement.

Utilize Ansible for configuration management and deployment automation.

Support and manage OpenShift environments, ensuring optimal performance and scalability.

Administer Linux servers, ensuring security, performance, and reliability.

Manage and configure Apache Tomcat servers for application deployment.

Implement and maintain monitoring tools to proactively identify and resolve issues.

Conduct log analysis to troubleshoot and optimize application performance.

Collaborate with cross-functional teams to enhance DevOps practices and tools.

Document processes, procedures, and best practices for infrastructure management.

Mandatory Skills:

Strong experience in application production support.

Proficiency in Python scripting for automation tasks.

Hands-on experience with Ansible for automation and orchestration.

Solid understanding of OpenShift and container orchestration.

Expertise in Linux administration, including server setup and maintenance.

Experience with Apache Tomcat configuration and management.

Familiarity with monitoring tools and log analysis techniques.

Knowledge of DevOps tools and practices.

Preferred Skills:

Experience with cloud platforms (AWS, Azure, GCP).

Familiarity with CI/CD pipelines and tools.

Knowledge of networking concepts and security best practices.

Experience with database management and optimization.

Understanding of Agile methodologies and practices.

Qualifications:

Bachelor's degree in Computer Science, Information Technology, or a related field.

Relevant certifications in cloud technologies, DevOps, or system administration are a plus.

Strong analytical and problem-solving skills.

Excellent communication and collaboration abilities.

Ability to work in a fast-paced environment and manage multiple priorities

What You Will Do

• Develop models and run experiments to infer insights from hard data
• Improve our product usability and identify new growth opportunities
• Understand reseller preferences to provide them with the most relevant products
• Designing discount programs to help our resellers sell more
• Help resellers better recognise end-customer preferences to improve their revenue
• Use data to identify bottlenecks that will help our suppliers meet their SLA requirements
• Model seasonal demand to predict key organisational metrics
• Mentor junior data scientists in the team

What You Will Need

• Bachelor's/Master's degree in computer science (or similar degrees)
• 4-7 years of experience as a Data Scientist in a fast-paced organization, preferably B2C
• Familiarity with Neural Networks, Machine Learning etc.
• Familiarity with tools like SQL, R, Python, etc.
• Strong understanding of Statistics and Linear Algebra
• Strong understanding of hypothesis/model testing and ability to identify common model testing errors
• Experience designing and running A/B tests and drawing insights from them
• Proficiency in machine learning algorithms
• Excellent analytical skills to fetch data from reliable sources to generate accurate insights
• Experience in tech and product teams is a plus

Bonus Points For

• Experience in working on personalization or other ML problems
• Familiarity with Big Data tech stacks like Apache Spark, Hadoop, Redshift

Key Responsibilities:

·       Design, develop, and maintain scalable data warehouse solutions using Snowflake.

·       Write, optimize, troubleshoot, and enhance Snowflake SQL queries with a focus on performance and scalability.

·       Develop and support ETL processes using Talend to ensure reliable and efficient data movement.

·       Collaborate with business, analytics, and application teams to enable reporting, dashboards, metrics, and data exploration capabilities.

·       Perform data analysis and resolve issues across data ingestion, transformation, and reporting pipelines.

·       Debug and troubleshoot Python-based data processing scripts and automation workflows.

·       Implement best practices for data quality, testing, deployment, and code reviews.

·       Work across UI, API, and Data Warehouse layers to support end-to-end data integration and business requirements.

·       Monitor, optimize, and maintain data warehouse performance and operational stability.

·       Create and maintain technical documentation, data models, and process workflows.

Required Skills and Experience: 

·       Strong hands-on expertise in Snowflake Data Warehouse.

·       Advanced SQL skills with experience handling large-scale datasets.

·       Strong understanding of Data Warehousing concepts, dimensional modelling, and data architecture.

·       Hands-on experience with Analytical SQL functions, query tuning, and performance optimization.

·       Experience developing and maintaining ETL solutions using Talend.

·       Proficiency in Python for scripting, debugging, automation, and data processing.

·       Experience integrating UI, API, and Data Warehouse workflows.

·       Strong problem-solving and analytical skills.

·       Experience with testing, code reviews, and deployment best practices.

·       Excellent communication and stakeholder management skills.

Job Summary

We are seeking an experienced Agentic AI Architect to design and build enterprise-scale Agentic AI platforms that enable autonomous, intelligent, and collaborative AI agents. The ideal candidate will drive architecture, technology strategy, and AI engineering best practices while delivering scalable, secure, and production-ready AI solutions.

Key Responsibilities

• Design enterprise architecture and technical roadmap for Agentic AI platforms.
• Build scalable multi-agent AI systems with reasoning, planning, memory, and autonomous decision-making capabilities.
• Architect solutions using LLMs, RAG, vector databases, embeddings, prompt engineering, orchestration frameworks, and agent execution engines.
• Design reusable frameworks for agent orchestration, lifecycle management, governance, observability, and monitoring.
• Integrate AI platforms with enterprise applications, APIs, databases, messaging systems, and cloud services.
• Implement AI security, governance, privacy, compliance, guardrails, and Responsible AI practices.
• Evaluate and implement frameworks such as Google ADK, LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, and MCP.
• Lead architecture reviews, technical governance, design workshops, and solution validation.
• Develop Proof of Concepts (PoCs) to evaluate emerging AI technologies.
• Mentor engineering teams and establish architecture standards and best practices.
• Collaborate with Product, AI/ML, Data Engineering, Cloud, DevOps, and Security teams.
• Drive AI platform scalability, modernization, performance optimization, and cost efficiency.

Required Skills

• Strong expertise in Agentic AI architecture and enterprise AI solution design.
• Hands-on experience with Large Language Models (GPT, Gemini, Claude, Llama, Mistral).
• Strong knowledge of RAG, Vector Databases, Embeddings, Prompt Engineering, AI Memory, Knowledge Graphs, and AI Orchestration.
• Experience with Google ADK, LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, MCP, or similar frameworks.
• Strong Python programming skills.
• Experience with FastAPI, REST APIs, Microservices, Distributed Systems, Event-Driven Architecture, Docker, Kubernetes, CI/CD, Git, and Azure/AWS/GCP.
• Knowledge of MLOps, LLMOps, AI Observability, monitoring, and production deployments.
• Strong understanding of AI Security, Governance, Responsible AI, and Enterprise Architecture.

Qualifications

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Software Engineering, or a related field.
• 10+ years of software engineering experience.
• 5–7+ years of experience designing enterprise AI/ML platforms and distributed systems.
• Proven experience architecting production-grade Agentic AI solutions.

Preferred Experience

• Domain experience in Supply Chain, Manufacturing, Retail, Healthcare, Financial Services, or Enterprise Automation.
• Experience building multi-agent collaboration systems.
• Knowledge of AI Governance and Responsible AI.
• Enterprise Architecture and Cloud Certifications are preferred.

Role: Senior Engineer (Cloud Cost Optimization Engineer – Azure FinOps)

Employment Type: Permanent with VDart Digital

Work Location: Remote

Project Description -

Identify and implement cost optimization opportunities across Azure, Databricks, Snowflake, Power BI, and enterprise data platforms.

Drive resource rightsizing, utilization improvements, and governance initiatives.

Build automation, monitoring, and proactive cost controls.

Implement FinOps best practices, cost allocation models, and optimization guardrails.

Partner with engineering and business teams to deliver sustainable cloud savings.

Develop dashboards, reporting, and executive insights on cloud spend and optimization opportunities.

Agentic AI Automation for all the above use cases

Key Skills

• Cloud Cost Optimization & FinOps

• Azure Cost Management

• Databricks Optimization (Photon, Spot Instances, Auto-Termination)

• Snowflake Warehouse & Storage Optimization

• Power BI Capacity Optimization

• Python / PowerShell Automation

• Terraform / Infrastructure as Code

• Azure DevOps & CI/CD

• Resource Rightsizing & Capacity Planning

• Cost Governance, Azure Policy & RBAC

• Cost Analytics, Reporting & Forecasting

Preferred Experience

• 5+ years of experience in Cloud Engineering, Platform Engineering, FinOps, DevOps, or Infrastructure Optimization.

• Hands-on experience with Azure and enterprise-scale cloud environments.

• Proven track record of delivering measurable cloud cost savings and optimization outcomes.

About ZYSYGY

ZYSYGY is building Germany's zero-fee payment network. Merchants pay zero transaction fees. We route payments directly over SEPA Instant, bypassing Visa, Mastercard, and the entire card network chain. No hardware. No card reader. Just a phone.

We are building the first company to combine a fully software-based merchant POS with a consumer super-app for everyday financial life: payments, transport, utilities, government services, all in one place. Think what UPI did for India. We are doing it for Germany, from the ground up, on banking rails.

Role Overview

You will join the core engineering team as a founding engineer. You will own the backend payment engine end to end: transaction flows, wallet management, SEPA Instant settlement, KYB/KYC integration, recurring mandates, refund logic, and the compliance export layer (DATEV, Kassenbuch, GoBD, fiskaltrust). On mobile, you will contribute to the React Native consumer and merchant apps alongside our mobile engineer.

You will own what you build from development through deployment, monitoring, and production reliability. The architecture decisions you make in the first six months will run in production for years.

What you will do

Design and build the backend payment engine: transaction flows, wallet management, SEPA Instant settlement, offline payment authorization, and recurring mandate billing.

Own KYB/KYC integration and the compliance export layer: DATEV, Kassenbuch, GoBD, and fiskaltrust for KassenSichV.

Build REST APIs for financial-grade reliability and high-throughput transaction processing, including full R-transaction handling and reconciliation pipelines.

Contribute to the React Native consumer and merchant mobile apps alongside our mobile engineer.

Own the full lifecycle of what you build, from development through deployment, monitoring, and continuous improvement.

Integrate AI tooling into your development workflow as a matter of course: code generation, automated testing, and intelligent review.

Who you are

Meaningful hands-on experience building payment systems, fintech infrastructure, or financial APIs.

You have designed a ledger. You understand double-entry bookkeeping, immutable transaction records, and why you never update a financial row.

You have solved the partial failure. Money left one wallet and did not arrive in the other. You know how to detect it, resolve it, and make sure it does not happen again.

You understand idempotency at a design level. You have built systems that survive client retries, duplicate webhooks, and network drops without double-charging anyone.

You have built or reasoned about reconciliation: detecting discrepancies between your internal ledger and an external settlement file, and resolving them reliably at scale.

You understand KYC and KYB state machines, what happens when verification status changes mid-transaction, and what a regulator expects from your audit trail.

You are comfortable with SQL databases and own the full lifecycle of your code from development through deployment.

You can communicate technical decisions clearly to non-technical stakeholders. At this stage of the company, that matters.

You are a continuous learner. Payments infrastructure is a deep domain and you treat it that way.

You are comfortable with ambiguity and early-stage risk. There is no playbook yet. You will help write it.

Strong academic background preferred. Demonstrated engineering ability matters more than institution.

Relocation

Relocation to Munich, Germany, is on the table for the right candidate, including visa support.

Connect with the Founder

You can also connect with me on LinkedIn at www.linkedin.com/in/shabbir-maimoon

Software Development Team Lead (Python & AI/ML)

Company: 75WAY Technologies Pvt. Ltd.

Location: Phase 8B, Mohali (Work from Office)

Experience: 4+ Years in Leadership

75WAY Technologies Pvt. Ltd. is looking for an experienced Software Development Team Lead with strong expertise in Python and AI/ML technologies. The ideal candidate will lead a team of developers, mentor engineers, and ensure the successful delivery of high-quality software solutions. Exposure to the MERN stack is preferred, but deep expertise is not mandatory.

Key Responsibilities

• Lead and mentor a team of software developers working on Python, AI/ML, and web application projects.
• Plan, assign, and monitor development tasks to ensure timely project delivery.
• Review code and maintain high standards for software quality, security, and performance.
• Collaborate with Project Managers, Business Analysts, QA Engineers, and UI/UX Designers to deliver scalable solutions.
• Design and develop robust backend applications using Python frameworks such as Django or FastAPI.
• Guide the implementation of AI/ML models and their integration into production applications.
• Participate in architecture discussions and technical decision-making.
• Resolve technical challenges and provide guidance to development teams.
• Conduct technical interviews, mentor junior developers, and support their professional growth.
• Ensure adherence to Agile/Scrum development methodologies and best coding practices.
• Stay updated with emerging technologies, AI advancements, and software development trends.

Job Summary

We are seeking a highly skilled and experienced Senior Salesforce QA Engineer to lead the end-to-end quality assurance for our enterprise Salesforce platform. In this role, you will design robust test strategies, establish automated testing pipelines, and validate complex custom configurations, Apex code, and integrations. As a senior member of the team, you will bridge the gap between business requirements and technical execution, ensuring the delivery of high-quality, scalable solutions across Sales, Service, and Custom Clouds.

Key Responsibilities

• Test Strategy & Planning: Define, implement, and maintain comprehensive test strategies, test plans, and test cases covering functional, regression, integration, and end-to-end scenarios.

• Test Automation: Architect, scale, and maintain automated testing frameworks using enterprise tools (e.g., Provar, Tricentis Tosca, or Selenium with Java/Python) specifically optimized for Salesforce's dynamic UI.

• Complex Custom Validation: Validate complex programmatic customizations (Apex classes, Triggers, Lightning Web Components) and declarative features (Advanced Flows, Validation Rules).

• Integration Testing: Lead end-to-end API testing (REST/SOAP) to verify seamless data flow between Salesforce and upstream/downstream external systems.

• Environment & Release Management: Oversee sandbox deployments, data masking, and regression testing during Salesforce seasonal releases and monthly deployment cycles.

• Defect Lifecycle Management: Own the defect tracking process in Jira or Azure DevOps, collaborating closely with developers, business analysts, and product owners for rapid root-cause resolution.

• Mentorship & Leadership: Provide technical guidance and mentorship to junior QA engineers and lead user acceptance testing (UAT) phases with business stakeholders.

Required Technical Skills & Qualifications

• Experience: 5 to 10 years of dedicated software quality engineering experience, with a minimum of 3+ years focused exclusively on testing Salesforce ecosystems.

• Salesforce Core Knowledge: Deep understanding of Salesforce architecture, data models, object relationships, sharing rules, and platform governor limits.

• Automation Expertise: Hands-on experience developing framework code or no-code architectures using tools like Provar, Selenium WebDriver, Tricentis Tosca, or UFT.

• API Testing: Proficient in API testing tools such as Postman, SoapUI, or automated API frameworks.

• Agile & Devops: Strong experience working within Agile/Scrum methodologies and integrating automated tests into CI/CD pipelines (e.g., Copado, Jenkins, GitHubActions).

• Data Management: Proficiency in writing SQL queries and utilizing Salesforce Data Loader for test data creation and verification.

We are seeking a Technology Solutions Engineer with 3–5 years of hands-on software development experience who is passionate about exploring new technologies and solving business problems through rapid prototyping. The role focuses on evaluating technology solutions, building proof-of-concept (POC) applications, validating third-party integrations, and assessing the technical feasibility of business requirements before production implementation.

Responsibilities:

• Understand business requirements and convert them into technical solution options.
• Research, evaluate, and compare SaaS products, AI platforms, cloud services, and enterprise applications.
• Develop POCs and prototypes to validate technical feasibility.
• Build and test integrations using REST APIs, webhooks, SDKs, and authentication mechanisms.
• Perform technical, scalability, security, and cost feasibility assessments.
• Prepare solution comparison reports, architecture diagrams, and technical recommendations.
• Collaborate with business users, vendors, and engineering teams during evaluations.
• Identify technical risks, assumptions, and implementation dependencies.
• Support engineering teams in transitioning successful POCs into production.
• Maintain clear technical documentation.

Criteria:

·      Bachelor's degree in Computer Science, Information Technology, or a related field.

·      3–5 years of hands-on experience in software development, integration engineering, or solution engineering.

·      Strong coding skills in Python, Node.js, Java, or C#.

·      Experience working with REST APIs, JSON, OAuth, webhooks, and API testing tools.

·      Hands-on exposure to AWS or another major cloud platform.

·      Experience with Git, Docker, and SQL databases.

·      Excellent analytical, troubleshooting, and communication skills

·      Comfortable collaborating across product, engineering, and business teams

·      Excellent communication, problem-solving, and stakeholder management skills.

Preferred Skills

• Exposure to OpenAI, Gemini, Claude, or other AI/LLM platforms.
• Experience evaluating third-party enterprise software.
• Basic knowledge of Kubernetes, Terraform, CI/CD, Redis, or Kafka.
• Ability to create architecture diagrams and technical proposals.

What Makes You Successful

• Quickly builds functional POCs to validate ideas.
• Can independently evaluate multiple technical approaches.
• Balances technical quality, implementation effort, and business value.
• Communicates findings clearly to technical and non-technical stakeholders.

Job Title : AI Agent / Agentic Engineer

Experience : 4+ Years

Employment Type : Contract

Role Level : Mid–Senior

Project : Leading South Africa Telecommunications Operator

Department : Data & AI Engineering

Job Overview :

We are looking for an experienced AI Agent / Agentic Engineer to design, develop, and deploy intelligent AI agents that automate business workflows and enhance data-driven decision-making.

The ideal candidate will have hands-on experience building autonomous or semi-autonomous AI systems using modern agent frameworks, integrating enterprise APIs, and deploying production-ready agentic solutions with strong safety and governance practices.

Mandatory Skills :

Python, AI Agents, LangGraph, CrewAI, AutoGen, Semantic Kernel, Multi-Agent Systems, Tool Calling, REST APIs, LLMs, RAG, Prompt Engineering, Agent Guardrails, Azure OpenAI (Preferred).

Key Responsibilities :

• Design and develop AI agents for workflow automation and business analytics.
• Build multi-step reasoning, planning, and tool-calling workflows using modern agent frameworks.
• Integrate AI agents with enterprise APIs, databases, and business applications.
• Implement agent guardrails, permission controls, human-in-the-loop workflows, and monitoring.
• Collaborate with GenAI, API, MLOps, and Data Engineering teams to deliver scalable AI solutions.
• Optimize agent performance, reliability, latency, and operational cost.
• Document AI agent capabilities, limitations, and deployment processes.

Required Skills :

• 4+ years of experience in Software Engineering or AI Engineering.
• Strong programming skills in Python.
• Hands-on experience with AI agent frameworks such as LangGraph, CrewAI, AutoGen, or Semantic Kernel.
• Experience building autonomous or semi-autonomous AI agents with multi-step reasoning and tool calling.
• Experience integrating AI solutions with REST APIs, enterprise systems, and data platforms.
• Understanding of LLMs, RAG concepts, prompt engineering, and AI agent orchestration.
• Knowledge of AI safety, guardrails, monitoring, and human-in-the-loop workflows.
• Experience deploying production-ready AI applications.

Good to Have :

• Experience with Azure OpenAI, Azure AI Foundry, or Azure AI Agent Service.
• Exposure to telecom, analytics, or enterprise AI solutions.
• Knowledge of cloud platforms, MLOps, and AI deployment best practices.

Company Name – Wissen Technology

Group of companies in India – Wissen Technology & Wissen Infotech

Work Location – Whitefield, Bangalore

While you may already know about Wissen and the company history, here is a quick rundown for you.

About Wissen Technology:

·    The Wissen Group was founded in the year 2000. Wissen Technology, a part of Wissen Group, was established in the year 2015.

·    Wissen Technology is a specialized technology company that delivers high-end consulting for organizations in the Banking & Finance, Telecom, and Healthcare domains. We help clients build world class products.

·    Our workforce has highly skilled professionals, with leadership and senior management executives who have graduated from Ivy League Universities like Wharton, MIT, IITs, IIMs, and NITs and with rich work experience in some of the biggest companies in the world.

·    Wissen Technology has grown its revenues by 400% in these five years without any external funding or investments.

·    Globally present with offices US, India, UK, Australia, Mexico, and Canada.

·    We offer an array of services including Application Development, Artificial Intelligence & Machine Learning, Big Data & Analytics, Visualization & Business Intelligence, Robotic Process Automation, Cloud, Mobility, Agile & DevOps, Quality Assurance & Test Automation.

·    Wissen Technology has been certified as a Great Place to Work®.

·    Wissen Technology has been voted as the Top 20 AI/ML vendor by CIO Insider in 2020.

·    Over the years, Wissen Group has successfully delivered $650 million worth of projects for more than 20 of the Fortune 500 companies.

·    We have served client across sectors like Banking, Telecom, Healthcare, Manufacturing, and Energy. They include likes of Morgan Stanley, Goldman Sachs, MSCI, StateStreet, Flipkart, Swiggy, Trafigura, GE to name a few.

Job Title: Azure Fabric Data Engineer / AI Engineer

Experience: 4–8 Years

Location: Pune(Hybrid)

Job Summary

We are seeking Azure Fabric Data Engineers with experience in data engineering, Power BI, and AI to build modern data platforms and AI-driven solutions on Microsoft Fabric.

Key Responsibilities

• Develop ETL/ELT pipelines using Microsoft Fabric.
• Integrate data from multiple enterprise systems into Fabric.
• Build and optimize Lakehouse and Data Warehouse solutions.
• Develop Power BI dashboards and reports.
• Build AI-powered applications, AI Agents, and chatbots using Azure AI Services and Azure OpenAI.
• Collaborate with business and technical teams to deliver scalable analytics solutions.

Required Skills

• Microsoft Fabric
• Data Engineering and ETL/ELT
• SQL, Python, PySpark
• Power BI
• Azure AI Services / Azure OpenAI
• Data Modeling
• Git and Azure DevOps

Preferred: Experience with Financial Services/Capital Markets, Generative AI, RAG, or LLM-based applications.

Job Description:

Required Skills

• Experience-4+ years
• Strong backend engineering fundamentals.
• Good understanding of system design concepts for scalable and reliable applications.
• Hands-on experience with at least one backend language such as Golang, Node.js, Java, Rust, Python, or similar.
• Strong understanding of REST APIs, service design, authentication, authorization, and API security.
• Good knowledge of database design, indexing, query optimisation, transactions, and data consistency.
• Experience with SQL databases such as PostgreSQL, MySQL, or similar.
• Understanding of NoSQL databases, caching systems, and when to use them.
• Experience working with Redis or similar caching technologies.
• Understanding of message queues, event-driven architecture, asynchronous processing, and background jobs.
• Ability to reason about memory management, garbage collection, concurrency, and runtime behaviour.
• Experience debugging performance issues in backend systems.
• Good understanding of high TPS systems, load testing, horizontal scaling, and bottleneck analysis.
• Familiarity with containerisation using Docker.
• Working understanding of Kubernetes-based deployments, preferably EKS.
• Understanding of CI/CD pipelines and cloud deployment practices.
• Good communication skills and ability to explain technical decisions clearly.

Good to Have Skills

• Experience with microservices architecture.
• Experience with AWS services, especially EKS, RDS, SQS, CloudWatch, ElastiCache, API Gateway, or Lambda.
• Understanding observability tools such as Prometheus, Grafana, Loki, Tempo, Open Telemetry, or similar.
• Experience with distributed tracing and production monitoring.
• Experience with event streaming platforms such as Kafka.
• Knowledge of security best practices around JWT, OAuth2, RBAC, secrets management, and secure API design.
• Experience designing systems for high availability and fault tolerance.
• Exposure to infrastructure-as-code tools such as Terraform or CloudFormation.
• Experience mentoring junior engineers or reviewing technical designs.

🚀 We're Hiring | Site Reliability Engineer (SRE)

📍 Location: Hyderabad (Hybrid)

💼 Experience: 4–6 Years

P99Soft is looking for a skilled Site Reliability Engineer (SRE) to join our engineering team. If you're passionate about building highly available, scalable cloud infrastructure and driving automation across modern DevOps environments, we'd love to hear from you.

Key Responsibilities

- Design, implement, maintain, monitor, and support backend servers and microservices infrastructure.

- Build and maintain automation tools for development, testing, operations, and IT infrastructure.

- Participate in 24/7 on-call support for production incidents (PagerDuty).

- Collaborate with cross-functional teams to ensure seamless deployments and operational excellence.

- Define and improve SRE processes across development, testing, releases, and support.

- Troubleshoot complex infrastructure and production issues.

- Drive infrastructure automation and continuous process improvements.

Implement security best practices, vulnerability assessments, and risk management.

- Perform incident management and root cause analysis (RCA).

- Monitor system health, customer experience, and operational KPIs.

Required Skills

- Cloud Platforms: AWS, GCP

- Containerization & Orchestration: Docker, Kubernetes, Rancher, Amazon EKS, Amazon ECS, GKE, Elastic Beanstalk, Google App Engine

- Infrastructure as Code (IaC): Terraform, AWS CloudFormation, GCP Deployment Manager, Ansible

- Monitoring & Observability: Prometheus, Datadog, Alertmanager, Thanos, AWS CloudWatch

- CI/CD: GitLab CI/CD, Jenkins

- Scripting: Python, Golang

- Version Control: GitLab, Perforce, Subversion

- Operating Systems: Ubuntu, CentOS, Amazon Linux, Red Hat Enterprise Linux

If you have hands-on experience managing cloud-native infrastructure, Kubernetes environments, DevOps automation, and production operations, we'd love to connect with you.

📩 Share your resume:

Know someone who would be a great fit? Feel free to like, share, or tag them in the comments.

#Hiring #SiteReliabilityEngineer #SRE #CloudEngineer #DevOps #AWS #GCP #Kubernetes #Docker #Terraform #Jenkins #GitLab #Python #Golang #Infrastructure #CloudComputing #HyderabadJobs #HybridJobs #TechJobs #P99Soft

Job Description:

We are looking for a highly skilled and experienced Python Developer to join our dynamic team. The ideal candidate will have a robust background in developing web applications using Django and Flask, with experience in deploying and managing applications on AWS. Proficiency in Django Rest Framework (DRF) and a solid understanding of machine learning concepts and their practical applications are essential.

Key Responsibilities:

• Develop and maintain web applications using Django and Flask frameworks.
• Design and implement RESTful APIs using Django Rest Framework (DRF).
• Deploy, manage, and optimize applications on AWS.
• Develop and maintain APIs for AI/ML models and integrate them into existing systems.
• Create and deploy scalable AI and ML models using Python.
• Ensure the scalability, performance, and reliability of applications.
• Write clean, maintainable, and efficient code following best practices.
• Perform code reviews and provide constructive feedback to peers.
• Troubleshoot and debug applications, identifying and fixing issues in a timely manner.
• Stay up-to-date with the latest industry trends and technologies to ensure our applications remain current and competitive.

Required Skills and Qualifications:

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• 3+ years of professional experience as a Python Developer.
• Proficient in Python with a strong understanding of its ecosystem.
• Extensive experience with Django and Flask frameworks.
• Hands-on experience with AWS services, including but not limited to EC2, S3, RDS, Lambda, and CloudFormation.
• Strong knowledge of Django Rest Framework (DRF) for building APIs.
• Experience with machine learning libraries and frameworks, such as scikit-learn, TensorFlow, or PyTorch.
• Solid understanding of SQL and NoSQL databases (e.g., PostgreSQL, MongoDB).
• Familiarity with front-end technologies (e.g., JavaScript, HTML, CSS) is a plus.
• Excellent problem-solving skills and the ability to work independently and as part of a team.
• Strong communication skills and the ability to articulate complex technical concepts to non-technical stakeholders.

We’re looking for a hands-on builder who can thrive in a fast-paced startup environment. You’ll own features end-to-end, from designing architecture to writing clean, reusable code, testing, deploying, and iterating fast.

What you’ll do

• Build and scale web + mobile applications using Python (Django) and React Native/React.
• Design, develop, and deploy cloud-native solutions using AWS services.
• Work with both SQL and NoSQL databases (PostgreSQL, DynamoDB).
• Ensure applications are secure, scalable, and performance-optimized.
• Collaborate closely with product, design, and business teams to ship features at lightning speed.
• Take ownership of problems - from brainstorming and architecture to debugging in production.
• Bring startup energy: move fast, learn fast, and don’t be afraid to get your hands dirty.

What we’re looking for

• 1-3 years of experience in full-stack development.
• Strong experience in Python (Django).
• Proficiency in React Native/React, with solid knowledge of JavaScript.
• Experience with AWS services (serverless, EC2, S3, etc.).
• Experience with docker or kubernetes.
• Hands-on with databases: PostgreSQL, DynamoDB.
• Strong understanding of data structures, design patterns, and microservices architecture.
• Proficiency with Git and version control workflows.
• A product-first mindset, balancing code quality with speed of execution.
• Great communication skills, detail-oriented, and a true team player.
• Bonus - If you are an AI native developer and try to solve problems using AI

We are looking for an Engineering Lead to own the entire technology stack — from onboarding and underwriting to disbursals, repayments, and collections — and to build the engineering function into something genuinely AI-native. 

What You'll Own 

● Full tech stack: backend, frontend, infrastructure, integrations, and data pipelines 

● Real-time underwriting and decisioning systems 

● LOS/LMS architecture — onboarding, disbursals, repayments, and collections

● Integrations with bureaus, KYC providers, account aggregators, and payment gateways 

● Reconciliation systems — disbursement, repayment, and NACH reconciliation end-to-end 

● AWS infrastructure: scaling, reliability, uptime, and cloud cost ownership ● Data infrastructure for the credit and risk team — feature pipelines, model serving, experiment infrastructure 

● Engineering leadership: hiring, sprint planning, code reviews, and execution standards 

● Compliance systems: RBI guidelines, DPDP, KYC/AML, e-NACH, e-sign 

AI-Native Engineering 

This is a core part of the role, not a bonus. You will build a machine-readable knowledge base of the entire codebase — architecture, data models, service contracts, coding standards, decision history — so that AI agents working on code have the context to produce accurate, consistent output. You will build skills for code review, developer onboarding, and recurring engineering workflows. You will build a code review pipeline where agents do the first pass on every pull request. The knowledge base and the skills improve over time as the team grows and the product evolves. 

What We're Looking For 

● 7+ years in software engineering, with at least 2 years leading teams or architecture

● Strong hands-on experience with Python, Django, and React Native

● Deep expertise in AWS and cloud-native architecture 

● Experience with both SQL and NoSQL databases 

● Strong understanding of distributed systems, microservices, and API design

● Experience owning reconciliation or payment flow infrastructure in a lending or payments context

● Prior experience in fintech / NBFC / digital lending — mandatory

● Strong understanding of the full loan lifecycle — mandatory 

● You have used LLMs seriously as engineering tools and have strong opinions about what makes AI-assisted development produce good output versus mediocre output 

Bonus: Kubernetes / Kafka, AI/ML-driven underwriting, Account Aggregator framework, e-NACH / e-Sign / Video KYC integrations 

What Success Looks Like 

● scales with strong uptime, performance, and reliability

● Reconciliation runs cleanly — no financial discrepancies surface late ● A new engineer joins and is writing standard, correct code within their first week

● The credit team is never blocked on an engineering dependency 

● Engineering health metrics are tracked and visibly improving 

● AI agents are doing the structured first pass on code reviews, and the system gets smarter over time 

Senior Gen AI Full Stack Engineer:

• Strong background in AI/ML and Gen AI with a deep understanding of LLMs, NLP pipelines, and AI model lifecycle.

• Experience in designing and building guardrail systems for Gen AI applications – including prompt filtering, semantic validation, toxicity detection, and hallucination mitigation.

• Fast API experience for API development.

• Proficiency in Python with frameworks like LangChain, Transformers, OpenAI, and LLM orchestration tools.

• Strong DevOps skills including CI/CD, Docker, Kubernetes, and Git.

Experience integrating Gen AI models into enterprise platforms securely and ethically.

Role: Full Stack GEN AI Engineer

Location: Remote - Bengaluru

Duration: Fulltime With VDart Digital

The role demands a developer who is not just familiar with Large Language Models (LLMs), but is an expert in building autonomous agentic workflows using the modern GenAI stack (LangChain, CrewAI, Vector DBs). Expertise in system design, cloud-native technologies, and CI/CD for AI-driven applications is essential for this high-impact delivery role.

Responsibilities

· Design, develop, and maintain full-stack applications that are scalable, robust, and meet the company's quality standards, with a specific focus on Generative AI integration.

· Agentic Orchestration: Build and deploy sophisticated multi-agent systems and autonomous workflows using frameworks like LangChain, CrewAI, or LangGraph.

· Collaborate effectively with cross-functional teams to define, design, and ship new features that bridge the gap between raw AI power and intuitive user workflows.

· Exhibit strong problem-solving skills with an emphasis on product development and driving architecture choices that enable a world-class user experience.

· Utilize a variety of modern web technologies and frameworks (React.js, Angular, or Vue.js) to build responsive and accessible user interfaces.

· Develop and maintain RESTful APIs and services with optimal performance and scalability, handling streaming AI responses and complex function-calling logic.

· Ensure code quality, organization, and automatization through best practices, including unit tests for prompts, model evaluation pipelines, and automated CI/CD for AI-driven features.

· Implement and optimize RAG (Retrieval-Augmented Generation) pipelines using Vector Databases and advanced retrieval techniques.

· Adapt to emerging technologies and frameworks, specifically new GenAI tools and frontier models, and apply them to operational and business needs.

· Manage individual project priorities, deadlines, and deliverables with minimal supervision.

Skill Requirements

· Excellent oral and written communication skills, with the ability to articulate complex AI and technical ideas to both technical and non-technical audiences.

· Profound knowledge of application development, data structures, networking, operating systems, and DBMS.

· Strong proficiency in backend programming languages for API development such as Python, Java, JavaScript (Node.js), or Go.

· Expertise in front-end technologies and frameworks such as React.js, Angular, or Vue.js.

· GenAI & Agentic Tools: Deep hands-on experience with LangChain, CrewAI, or AutoGen. Ability to manage agent memory, state, and tool-calling.

· In-depth understanding of SQL/NoSQL databases, data modeling, and experience with Vector Databases for RAG implementations.

· Solid grasp of system design, microservices architecture, and cloud-native technologies including Docker, Kubernetes, and GitHub Actions.

· Experience with distributed computing, machine learning frameworks, and tools, with a primary focus on Generative AI.

· Desirable (Good to Have): Experience with Generative or Adaptive UI development, where the interface dynamically adapts or renders components based on LLM outputs and real-time AI reasoning.

· A strong desire to learn and master new technologies and techniques in the rapidly evolving GenAI landscape.

Qualifications

· Bachelor’s degree in Computer Science, Engineering, or a related field.

· A minimum of 3-5 years of experience in full-stack development, with a proven track record of building and deploying Generative AI applications and agents.

· Portfolio of successfully deployed web applications and services, specifically showcasing AI agents, RAG implementations, or complex AI-driven features.

On the Job

● Build and maintain scalable cloud infrastructure on AWS

● Improve CI/CD pipelines, deployment systems, and developer workflows

● Automate infrastructure provisioning using Infrastructure-as-Code (Terraform/Pulumi)

● Manage and optimize Kubernetes clusters and containerized workloads

● Improve observability across systems through monitoring, logging, and alerting

● Drive reliability initiatives including incident response, root cause analysis, and operational

improvements

● Collaborate with engineering teams to improve service scalability, performance, and security

● Implement IAM, secrets management, and infrastructure security best practices

● Optimize infrastructure costs and improve resource efficiency

● Actively leverage AI tools and workflows to improve engineering productivity and automation

Must Haves

● 3–6 years of experience in DevOps, Platform Engineering, or SRE roles

● Strong hands-on experience with AWS infrastructure and services

● Good understanding of Kubernetes, Docker, and container orchestration

● Experience with Infrastructure-as-Code tools like Terraform or Pulumi

● Strong scripting/coding skills in Python, Go, or Bash

● Experience building and maintaining CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI,

etc.)

● Understanding of networking fundamentals, Linux systems, and cloud security practices

● Familiarity with monitoring and observability tools like Prometheus, Grafana, ELK, Datadog,

etc.

● Strong debugging and problem-solving skills

● Ability to work independently in a fast-moving environment

Good To Haves

● Experience working in fintech or high-scale startup environments

● Exposure to service mesh, zero-trust security, or secrets management systems

● Experience with multi-cluster Kubernetes environments

● Familiarity with incident management, SLOs, and reliability engineering practices

● Experience building internal developer platforms or automation tooling

Who are we?

Securin is an AI-driven cybersecurity company focused on proactive, adversarial exposure and

vulnerability management. Our mission is to help organizations reduce cyber risk by identifying,

prioritising, and remediating the issues that matter most. Powered by a seasoned team of threat

researchers and status as a Certified Naming Authority (CNA), Securin combines artificial intelligence

/ machine learning, threat intelligence, and deep vulnerability research (including the Dark Web) to

deliver an adversarial approach to cyber defence. We help enterprises shift from reactive patching

to strategic, risk-based exposure and vulnerability management – driving smarter security decisions

and faster remediation.

What do we promise?

We are a highly effective tech-enabled cybersecurity solutions provider and promise continual

security posture improvement, enhanced attack surface visibility, and proactive prioritised

remediation for every one of our client businesses.

What do we provide?

● A chance to be on the leading edge of cybersecurity and AI

● Ability to have direct impact on company growth and revenue strategy

● An opportunity to mentor and be mentored by experts in multiple disciplines

What do we deliver?

Securin helps organizations to identify and remediate the most dangerous exposures, vulnerabilities,

and risks in their environment. We deliver predictive and definitive intelligence and facilitate

proactive remediation to help organizations stay a step ahead of attackers.

By utilising our cybersecurity solutions, our clients can have a proactive and holistic view of their

security posture and protect their assets from even the most advanced and dynamic attacks.

Securin has been recognized by national and international organizations for its role in accelerating

innovation in offensive and proactive security. Our combination of domain expertise, cutting-edge

technology, and advanced tech-enabled cybersecurity solutions has made Securin a leader in the

industry.

Key Responsibilities:

● Develop and maintain Python-based applications, ensuring high quality, performance, and

maintainability.

● Apply object-oriented programming (OOP) principles and best practices to design and

implement software solutions.

● Collaborate with cross-functional teams to understand project requirements and contribute

to technical discussions.

● Utilize NoSQL databases, particularly MongoDB, to store and retrieve data efficiently.

● Implement and adhere to test-driven development (TDD) methodologies, writing unit tests

and integration tests for robust and reliable code.

● Work closely with team members to review code, provide constructive feedback, and improve

overall code quality.

● Participate in agile development processes, including sprint planning, daily stand-ups, and

retrospectives.

● Communicate effectively with team members and stakeholders to discuss project updates,

challenges, and solutions.

● Demonstrate a proactive attitude towards learning new technologies and acquiring new skills

to enhance professional growth.

● Stay up to date with industry trends, emerging technologies, and best practices in Python

development.

● 5-7 years hands on experience who can lead architect for features/modules, Mentors others

and ensures code quality, Identifies improvements to patterns, architecture, processes and

handles tough problems independently preferred.

● Knowledge of version control systems (e.g., Git) and collaborative development workflows.

● Familiarity with Agile/Scrum methodologies.

Requirements:

● Can articulate and comprehend communications within and outside the team.

● Is participative and able to present information both verbally and in writing in a way that others can easily understand.

● Is able to communicate commitments, set expectations and meet those.

● Ensures that they have the appropriate context and background prior to presenting information.

● Solicits ideas and inputs from other team members.

● Actively pursues opportunities to develop skills.

● Regularly encourages and recognizes others.

● Consistently can be counted on to identify problems when they occur.

● Independently able to research alternatives or define what data is relevant and can collect

appropriate information to bring to the conversation.

● Is able to independently evaluate options and choose the best solution when making a recommendation.

● Seeks out customer requirements and works to meet customer expectations.

● Viewed as effective by the customer.

● Realizes that customer supplier relationships go both ways.

● Effectively leads and motivates a team, sets clear goals and expectations, delegates tasks, and

communicates effectively.

● Actively engages in mentoring relationships, providing guidance and support to mentees,

helping them develop their skills and achieve their goals.

● Identifies improvements to patterns, architecture, processes.

● Handles tough problems independently.

● Influences architecture decisions for product/tech depts.

● Comfortable using frameworks to develop applications, with the ability to configure and utilize

key features and functionalities.

● Able to design and implement database schemas, write complex SQL queries, and perform

basic database administration tasks.

● Able to identify and apply appropriate design patterns in code to solve specific problems,

following best practices.

● Can deploy and manage applications on cloud platforms, utilize cloud services like storage,

messaging, and compute, and understand cloud-native principles to new technologies.

● Strong problem-solving and analytical thinking abilities.

The AI Specialist candidate should have the following skills:

Must-have:

• Proficiency in Python and Java
• Experience with LLMs, prompt engineering, and RAG architectures
• Familiarity with AWS cloud platform
• Strong analytical and problem-solving skills
• Ability to communicate complex technical concepts to non-technical stakeholders

Hiring for Lead Python Developer

Exp : 7+ yrs

Edu : BE/B.Tech

Work Location : Bengaluru / Gurugram Hybrid

Skills :

Strong expertise in Python programming. 

Experience with frameworks such as: Django Flask FastAPI 

Strong understanding of: REST APIs Microservices Architecture OOPs Concepts Design Patterns 

Experience with databases: PostgreSQL MySQL MongoDB Redis 

Hands-on experience with: Docker Kubernetes CI/CD Pipelines Git/GitHub/GitLab 

Cloud platform experience: AWS / Azure / GCP 

Knowledge of message brokers: Kafka / RabbitMQ 

Experience with unit testing and automation frameworks. 

Leadership Skills Strong team handling and mentoring experience. 

Ability to drive technical discussions and architecture decisions. 

Excellent stakeholder management and communication skills. 

Experience managing Agile/Scrum teams. 

Preferred Qualifications Bachelor’s/Master’s degree in Computer Science or related field.

 Experience in large-scale enterprise applications.

Exposure to AI/ML integrations is an added advantage. Certifications in cloud or Python technologies are preferred.

About the company

The client is building an AI-native platform for modern law firms.

Legal work is evolving rapidly, but much of the industry's workflow continues to rely on fragmented software and manual processes. The team is building an intelligent platform that helps law firms streamline work across the entire legal lifecycle, including document screening, drafting, filing, research, compliance, and other high-value legal workflows.

Their founding team combines deep expertise across both law and technology, giving us a unique perspective on how AI can fundamentally reshape legal operations while maintaining the precision and reliability that the profession demands.

We're looking for engineers who want to build products from first principles, move quickly, and help define the future of AI in legal technology.

About the role

We're hiring a Founding Software Engineer to help build the core platform from the ground up.

This is a high-ownership role. You'll work across backend systems, AI infrastructure, product architecture, and deployment, collaborating directly with the founders to design and ship features that reach customers quickly.

If you enjoy solving hard engineering problems, shipping fast, and working in a small, ambitious team, we'd like to talk.

What You'll Build

• AI-powered legal workflows for law firms
• Agentic systems for drafting, screening, and legal document analysis
• Reliable backend services and APIs
• Retrieval and knowledge systems for legal intelligence
• Evaluation pipelines to improve AI quality and reliability
• Internal developer tooling and scalable platform infrastructure

What We're Looking For

• 1-2 years of software engineering experience
• Strong Proficiency in at least one backend language: Python (FastAPI or Django), or Node.js
• Experience working with at least one database: MongoDB, PostgreSQL, MySQL, or another relational database
• Understanding of modern AI application architecture, including concepts such as: Agentic systems AI SDKs Retrieval-Augmented Generation (RAG) Prompt engineering Evaluation frameworks (Evals)
• Strong system design and problem-solving skills
• Ability to ship production-quality software quickly
• High ownership and bias toward execution
• Comfortable learning new technologies as the product evolves

Nice to Have

• Experience building products in Compliance, FinTech, RegTech, or LegalTech
• Experience deploying and operating AI-powered production systems
• Familiarity with cloud platforms and modern deployment workflows
• Experience working in an early-stage startup

What We Value

• High agency
• Strong engineering fundamentals
• Curiosity and continuous learning
• Fast execution without compromising quality
• Clear communication and collaborative problem solving

Why Join Us

• You'll be joining at the earliest stage of the company and will help shape both the product and the engineering culture.
• This is an opportunity to work directly with founders who combine legal and technical expertise, solve meaningful problems for the legal industry, and build AI systems that are used every day by legal professionals.
• If building from zero excites you more than m

About the company

The client is building an AI-native platform for modern law firms.

Legal work is evolving rapidly, but much of the industry's workflow continues to rely on fragmented software and manual processes. The team is building an intelligent platform that helps law firms streamline work across the entire legal lifecycle, including document screening, drafting, filing, research, compliance, and other high-value legal workflows.

Their founding team combines deep expertise across both law and technology, giving us a unique perspective on how AI can fundamentally reshape legal operations while maintaining the precision and reliability that the profession demands.

We're looking for engineers who want to build products from first principles, move quickly, and help define the future of AI in legal technology.

About the role

We're hiring a Founding Software Engineer to help build the core platform from the ground up.

This is a high-ownership role. You'll work across backend systems, AI infrastructure, product architecture, and deployment, collaborating directly with the founders to design and ship features that reach customers quickly.

If you enjoy solving hard engineering problems, shipping fast, and working in a small, ambitious team, we'd like to talk.

What You'll Build

• AI-powered legal workflows for law firms
• Agentic systems for drafting, screening, and legal document analysis
• Reliable backend services and APIs
• Retrieval and knowledge systems for legal intelligence
• Evaluation pipelines to improve AI quality and reliability
• Internal developer tooling and scalable platform infrastructure

What We're Looking For

• 3-5 years of software engineering experience
• Strong Proficiency in at least one backend language: Python (FastAPI or Django), or Node.js
• Experience working with at least one database: MongoDB, PostgreSQL, MySQL, or another relational database
• Understanding of modern AI application architecture, including concepts such as: Agentic systems AI SDKs Retrieval-Augmented Generation (RAG) Prompt engineering Evaluation frameworks (Evals)
• Strong system design and problem-solving skills
• Ability to ship production-quality software quickly
• High ownership and bias toward execution
• Comfortable learning new technologies as the product evolves

Nice to Have

• Experience building products in Compliance, FinTech, RegTech, or LegalTech
• Experience deploying and operating AI-powered production systems
• Familiarity with cloud platforms and modern deployment workflows
• Experience working in an early-stage startup

What We Value

• High agency
• Strong engineering fundamentals
• Curiosity and continuous learning
• Fast execution without compromising quality
• Clear communication and collaborative problem solving

Why Join Us

• You'll be joining at the earliest stage of the company and will help shape both the product and the engineering culture.
• This is an opportunity to work directly with founders who combine legal and technical expertise, solve meaningful problems for the legal industry, and build AI systems that are used every day by legal professionals.
• If building from zero excites you more than maintaining legacy systems, we'd love to hear from you

Role overview:

We are hiring one Senior Backend Engineer to take end-to-end ownership of our serverless backend — a hands-on IC role for someone both technically excellent and comfortable being one of the few people the entire backend depends on. You'll own the services across several Node.js and Python repositories, work directly with the founders and product team, and set the technical bar for reliability, security, and performance.

Key responsibilities

• Design, build, and operate AWS Lambda services across our HCM/workforce, project-management, commercial/revenue, permissions, and document domains — each comprising dozens of functions.
• Own the multi-tenant PostgreSQL data layer — schema design, query performance, and the permission/relationship model — end to end.
• Maintain and evolve the request path — API Gateway → custom Lambda authorizer → VPC-bound Lambda → private databases — including the runtime IAM/credential model that scopes every request.
• Safeguard tenant isolation and security across a per-company Cognito authentication model.
• Build and maintain integrations with external construction data environments (Asite, Autodesk Construction Cloud), including large-scale document synchronization.
• Optimize performance and reliability to keep latency-sensitive endpoints well within platform limits under growing load.
• Raise the engineering bar — testing, observability, CI/CD, and modernization of legacy components.
• Debug and resolve production incidents to root cause, and put safeguards in place so they don't recur.
• Document decisions and designs and collaborate with the frontend (Angular) and product teams.

Challenges you'll solve.

We prefer to be candid — these are the problems that make this role genuinely interesting:

Latency under a hard ceiling

API Gateway terminates any request beyond ~29 seconds regardless of the Lambda's own timeout — yet much of our value comes from heavy cross-project reporting. You'll keep p95 latency within budget through set-based SQL, pagination, streaming, and asynchronous processing.

Least-privilege, per-request security

A shared custom authorizer mints short-lived, request-scoped credentials via sts:AssumeRole under a strict 2,048-character inline session-policy limit. You'll design permission models that stay within that budget and reason about IAM precisely.

Graph-shaped data, relational store

The permission and relationship model is inherently graph-like, but lives in PostgreSQL — you'll model it with recursive queries, careful indexing, and set-based traversal rather than reaching for a separate graph engine.

Watertight multi-tenancy

One Cognito pool per company and tenant-scoped access throughout — isolation is a first-order concern.

VPC-bound serverless

Lambdas run inside a VPC to reach private databases; you'll manage cold starts, connection lifecycles, and pool limits.

Resilient external integrations

Syncing large document sets from third-party APIs (including SOAP/XML) demands backpressure, deduplication, retries, and graceful partial-failure handling.

Compute-heavy workloads

Server-side PDF generation, image processing, and multi-currency handling within Lambda's memory and time constraints.

The stack.

Runtime — Node.js, Python, AWS Lambda

AWS services — -1 API Gateway, Lambda, Cognito, STS / IAM, Secrets Manager, S3 CloudWatch, VPC, EC2

Infrastructure & CI/CD- AWS SAM, CodePipeline → CodeBuild Shared Data —PostgreSQL

Qualifications.

• 5+ years building and operating production backend systems.
• Deep expertise in Node.js and JavaScript — the asynchronous model, event loop, and memory behavior — plus solid working proficiency in Python and its production behavior.
• Strong hands-on AWS experience, ideally serverless (Lambda, API Gateway, IAM/STS, VPC, Secrets Manager, CloudWatch) — able to reason about IAM policies, not just apply them.
• Advanced SQL and relational data modeling — set-based query design and a working understanding of why N+1 patterns cause production issues.
• Proven production-debugging ability — root-cause analysis in distributed systems from logs and first principles.
• Strong ownership, sound judgment, and clear written communication — able to make good decisions with incomplete information and explain trade-offs to non-engineers.

Interview Process:

Introductory call-Mutual fit and role overview.

Technical deep-dive- A walkthrough of a challenging production problem you have owned.

Practical exercise -A realistic backend task, or a walkthrough of your own representative code.

System design- Collaborative design on a real scenario.

Final conversation- Values, ownership, compensation, and offer.

Job Title: Frontend Developer

Location: Arjan Garh, MG Road (Delhi)

Job Type: Full-time, On site

**IMMEDIATE JOINERS REQUIRED**

About Us

Our Aim is to develop ‘More Data, More Opportunities’. We take pride in building cutting-edge AI solutions to help financial institutions mitigate risk and generate comprehensive data. We are looking for a talented Frontend Developer to join our dynamic team and contribute to that which makes a real impact.

Job Summary

We are looking for a creative and technically skilled Front-End Developer who can seamlessly blend UI/UX design principles with robust coding practices. The ideal candidate will collaborate with our development team to create visually appealing and user-friendly web applications.

Key Responsibilities

• UI/UX Implementation: Convert design prototypes (e.g., from Figma, Sketch) into pixel-perfect HTML/CSS. Ensure the design is responsive using CSS media queries, Grid, and Flexbox.
• Design and implement RESTful APIs or GraphQL endpoints using backend stacks such as Node.js (Express/Nest), Python (Django/Flask), Java (Spring Boot)
• Feature Development: Develop new user-facing features using HTML, CSS, and JavaScript. Build reusable code and libraries for future use.
• Cross-Functional Collaboration: Work closely with back-end developers to integrate UI components with server-side logic.
• Version Control: Use version control systems like Git to manage and review reusable, clean, and efficient code.
• Responsive Design: Develop websites that work across different screen sizes, from mobile phones to large desktops, by using a mobile-first approach and CSS methodologies.
• Testing and Debugging: Identify and resolve functionality issues to ensure smooth user experiences across various browsers and devices.
• Continuous Learning: Stay updated with emerging front-end technologies, best practices, and industry trends.

Qualifications

• Education: Bachelor's degree in Computer Science, Web Development, or a related field.

Required Skills and Experience:

• Minimum 2 years of software development experience—emphasis on frontend, but ideally exposure across full-stack development.
• Proficiency in HTML5, CSS3, and JavaScript.
• Experience with modern front-end and back end frameworks.
• Familiarity with version control systems such as Git.
• Familiarity with design tools such as Figma, Sketch, or Adobe XD.
• Knowledge of responsive design and cross-browser compatibility issues.

Soft Skills:

• Strong problem-solving skills and attention to detail.
• Excellent communication and teamwork abilities.
• Ability to work in a collaborative environment and meet deadlines.

Job Title : Python Backend Developer

Experience : 3 to 6 Years / 6 to 8 Years

Location : Remote

Shift : US Shift (7:30 PM IST – 4:30 AM IST)

Open Positions : 2

Job Summary :

We are looking for a skilled Python Backend Developer to design, develop, and maintain scalable backend applications and RESTful APIs.

The ideal candidate should have strong hands-on experience with Python, backend architecture, and database integration. Exposure to Jasper Reports and Oracle PL/SQL will be an added advantage.

Mandatory Skills :

Python, REST API Development, Backend Architecture, Relational Databases, Git (Jasper Reports & Oracle PL/SQL experience preferred).

Key Responsibilities :

• Develop and maintain backend applications using Python.
• Design and build scalable RESTful APIs and web services.
• Integrate applications with databases, internal systems, and third-party services.
• Develop and support reporting solutions using Jasper Reports.
• Write and maintain Oracle PL/SQL queries and procedures.
• Troubleshoot production issues and optimize application performance.
• Participate in code reviews, system design, and Agile development.

Required Skills :

• 3 to 8 years of backend development experience.
• Strong proficiency in Python.
• Experience with REST APIs, JSON, and HTTP.
• Good understanding of backend architecture and service-oriented design.
• Experience with relational databases and Git.
• Strong analytical and problem-solving skills.

Preferred Skills :

• FastAPI, Flask, or Django.
• Jasper Reports / Jaspersoft.
• Oracle & PL/SQL.
• AWS, Azure, or GCP.
• CI/CD and DevOps practices.

Job Title: Principal Automation Engineer (AI)

Deltek is seeking a Principal Automation Engineer with deep expertise in AI-native test automation to help shape the quality engineering foundation Deltek’s next-generation, AI-first ERP platform for project-based businesses. This is not a role for someone who automates feature regression. It is a role for someone who can harness AI tools to build intelligent automation frameworks that reason, adapt, and self-heal.

You will be the automation architect behind Deltek’s in-house AI-native test automation platform combining Playwright with LLM-powered agents (Planner, Generator, Healer). You will extend, evolve, and industrialize this framework, integrating AI tools at every layer: test generation, self-healing selectors, LLM-as-a-Judge evaluation, and CI/CD-gated quality pipelines.

If you are fluent in Playwright, agentic AI workflows, and modern test engineering — and want to build something genuinely new rather than maintain legacy frameworks — we invite you to join our team. ERP domain knowledge is a strong plus and will accelerate your impact.

Responsibilities:

Architect and evolve the AI-native automation framework — extending Playwright-based agents with LLM-powered planning, test generation, and self-healing capabilities.

Use AI tools extensively (Claude, GitHub Copilot, LLM APIs) to design, generate, and augment automation suites — reducing human authoring effort while increasing scenario coverage.

Build and maintain Playwright agent pipelines for end-to-end workflow automation across Deltek’s Projects, Workforce Management, and Financials modules.

Integrate LLM-as-a-Judge (LLMaaJ) evaluation into the test pipeline to automatically score AI-generated outputs, detect hallucinations, and validate response quality against golden datasets.

Design and implement AI safety and correctness test cases: hallucination detection, bias testing, output guardrail validation, and behavioral consistency across edge cases.

Own the CI/CD automation pipeline (GitHub Actions / Azure DevOps) for AI-enabled releases — including regression gates, model-response validation, and automated quality dashboards in ReportPortal and Grafana.

Validate AI/ML outputs including prediction accuracy, recommendation relevance, natural-language responses, and inference API payloads.

Build and maintain golden datasets for AI drift detection, regression baselines, and LLM evaluation benchmarks.

Collaborate with Product Managers, AI/ML Engineers, and QE leads to define AI feature release quality gates and automation coverage targets.

Mentor QE team members on AI-assisted automation patterns, agentic testing concepts, and framework best practices.

Contribute to test strategy for data migration validation of schema fidelity and record correctness.

Qualifications:

BS/MS degree in Computer Science, Software Engineering, or a related field.

Relevant certifications in software quality, AI/ML, or cloud engineering are advantageous.

Experience:

8+ years of experience in test automation engineering, with at least 3+ years working with AI/LLM-based systems or agentic automation frameworks.

Proven hands-on experience with Playwright — including Playwright agents, fixtures, and API testing integration.

Demonstrated experience using AI tools (Claude API, OpenAI, GitHub Copilot, or equivalent) to accelerate test authoring, framework design, or output evaluation.

Track record of designing and implementing AI-based automation solutions — not just using automation tools, but building the frameworks others use.

Experience integrating automation into CI/CD pipelines (GitHub Actions, Jenkins, or Azure DevOps).

Experience with performance, scalability, or data-drift testing of AI features in production or pre-production ERP contexts.

ERP domain knowledge (Project Accounting, Financials, Payroll, Time & Expense) is a strong plus and will significantly accelerate onboarding and impact.

Good-to-Have Skills:

Familiarity with Ajera, Costpoint, Vantagepoint, or comparable project-based ERP systems.

Understanding of LLM fine-tuning, RAG pipelines, vector databases, and embeddings from a QA/validation perspective.

Experience building or working with self-healing automation frameworks or AIOps tooling.

Exposure to security testing for AI systems — prompt injection, output sanitization, guardrail bypass testing.

Familiarity with data privacy and compliance frameworks in AI-enabled enterprise software.

Technical Qualifications:

Deep, hands-on proficiency with Playwright — including agentic patterns, multi-step workflow automation, and integration with LLM backends.

Proficiency in TypeScript and/or Python for building automation frameworks, AI evaluation utilities, prompt-testing harnesses, and data-driven test pipelines.

Strong understanding of LLM/ML concepts from a QA perspective: prompt engineering, hallucination detection, output scoring, explainability validation, behavioral consistency testing.

Experience with REST and GraphQL API testing, including automated evaluation of LLM inference API payloads and AI-generated JSON responses.

Familiarity with ReportPortal, Grafana, or equivalent for test execution dashboards and quality metric visualization.

Strong SQL skills for data validation, training dataset verification, and ERP data pipeline testing.

Working knowledge of GitHub Actions and Azure DevOps (ADO/TFS) for CI/CD pipeline integration and issue tracking.

Good understanding of Agile/Scrum practices and AI model release cycles — shadow mode, A/B comparison, phased rollout validation.

Soft Skills:

Framework-builder mindset: thinks in systems, not scripts — builds what others use rather than executing what others built.

Strong communication skills: able to explain AI validation concepts clearly to engineers, product managers, and QE team members.

High ownership and self-direction: identifies automation gaps proactively and drives coverage improvements without waiting to be asked.

Collaborative and generous with knowledge: invests in mentoring team members and raising the team’s automation maturity.

Continuous learner: actively tracks the evolving AI tooling ecosystem and brings new techniques into the framework.

Able to manage multiple priorities in a fast-paced, distributed team environment.

Join Deltek and be at the forefront of how modern ERP quality engineering is done. You will help build the AI driven current automation framework into an industry-leading AI-native automation platform — combining Playwright agents, LLM-powered test generation, self-healing infrastructure, and intelligent quality gates.

We're building in a market that hit $47B in 2026 and is on track to hit $107.5B by 2028 and we're not chasing that opportunity from the sidelines. Our founding team brings marketing expertise from Kotak and Amazon paired with deep AI chops, we were selected as one of just 20 startups by Google, and we already have paying customers like Kotak and Myntra using the product in production. Join us early and help build the infrastructure that turns AI marketing adoption (already at 88%) into real, scaled results for customers who are already paying for it, not case studies.

Founding Product Engineer, Applied AI

Location: Mumbai • Hybrid • Reports to: CTO

WHAT THIS ROLE ACTUALLY IS

Weve built a multi-agent AI system for marketing. It works well out of the box but every client (their data, workflows, brand rules, compliance constraints, output preferences) is different. Generic doesnt ship results. Customised does.

This role is the bridge: you sit between our agent architecture and the client’s reality. You understand both deeply, and you make the agents do what each specific client needs them to do.

Think Palantir Forward Deployed Engineer, but for AI agents. An engineer who owns product outcomes end-to-end.

WHAT YOU'LL DO

Day-to-day split: roughly 60% in Codex and Claude Code shipping customisations, 40% in client rooms understanding what to ship next.

• Customise the agents. Tune prompts, build new agent capabilities, configure workflows, wire up integrations. Codex and Claude Code are your primary IDEs. You ship working code, not specs for someone else to build.
• Own client outcomes end-to-end. From discovery to live deployment, you are the person responsible for whether the agents actually solve the client’s problem. No PM-engineer handoff to hide behind.
• Problem-solve in real time. Client says “the output tone is off for our brand” or “the research agent is missing X data source” — you diagnose, fix, and redeploy, usually within days.
• Hold your own on creative. When a CMO says “this doesn’t feel right,” you can question intelligently — is it the prompt, the input brief, the brand guidelines themselves, or the client’s own confusion? Most engineers reach for the prompt. The good ones diagnose first.
• Feed learnings back to core product. Anything that gets customised 3+ times becomes a platform feature. You decide what graduates.
• Build the playbook. As we scale from 10 to 50 to 100 clients, the customisation patterns you create become the foundation others work from.

WHAT YOU NEED

• Real engineering chops. You can read a codebase, write production code, debug agent failures, and ship to live clients. AI tools are your accelerant, not your crutch.
• Comfort with agents as a system. You understand how LLMs fail, why prompts drift, what context engineering means, when to use tools vs. fine-tuning, why eval harnesses matter. If “MCP,” “tool use,” and “agent harness” feel like jargon, this isn’t the role.
• Client-facing instincts. Comfortable in a room with a CMO, an enterprise IT head, and a junior brand manager — and you can switch register for each in the same meeting. If client calls feel like tax to you, don’t apply.
• Some creative literacy. You don’t need to be a designer. You do need to be able to tell the difference between “this output is technically broken” and “this output is technically fine but creatively wrong” — and chase the right thread.
• Bias toward shipping. A working hack today beats a clean design next quarter.

YOU'LL THRIVE HERE IF

• You’re an engineer who realised products live or die on customisation, not architecture.
• You’ve been frustrated by being kept away from customers.
• You like building with AI tools and want a role where that’s the job, not a side experiment.
• You like marketing as a domain — or you’re willing to fall in love with it.

YOU WON'T THRIVE HERE IF

• You want to optimise systems in a corner with headphones on.
• You think client calls are below your pay grade.
• You think AI is overhyped (we don’t).
• You need a fully scoped ticket queue and weekly sprint rituals.

About US:-

We turn customer challenges into growth opportunities.

Material is a global strategy partner to the world’s most recognizable brands and innovative companies. Our people around the globe thrive by helping organizations design and deliver rewarding customer experiences.

We use deep human insights, design innovation and data to create experiences powered by modern technology. Our approaches speed engagement and growth for the companies we work with and transform relationships between businesses and the people they serve.

Srijan, a Material company, is a renowned global digital engineering firm with a reputation for solving complex technology problems using their deep technology expertise and leveraging strategic partnerships with top-tier technology partners.

Job Description: Sr. Full Stack Engineer (Python, JavaScript & AI Engineering) – 7-8 years 

Role Summary 

We are seeking an experienced Sr. Engineer/Technical Lead with strong expertise in Python, JavaScript/TypeScript, and AI-native application development. The ideal candidate will build scalable cloud applications, architect intelligent systems powered by Large Language Models (LLMs), drive engineering excellence, and help teams adopt modern AI-assisted development practices. This is a hands-on leadership role combining software engineering, AI integration, and technical mentorship. 

Key Responsibilities 

• Design, develop, and maintain scalable applications using Python and JavaScript/TypeScript. 
• Build APIs, microservices, and event-driven cloud-native solutions. 
• Design and implement AI-enabled features using LLMs, RAG, structured outputs, and tool integrations. 
• Build and maintain agentic workflows for business automation and developer productivity. 
• Leverage AI coding assistants and code agents to improve software delivery and engineering efficiency. 
• Integrate enterprise services including authentication, SSO, authorization, and internal platforms. 
• Collaborate with platform teams to deploy and operate applications on AWS or Azure. 
• Drive engineering best practices including CI/CD, testing, observability, code reviews, and secure development. 
• Document architectures, APIs, AI workflows, and key technical decisions. 
• Mentor engineers and help teams adopt modern AI-first development practices. 

Required Skills 

• Strong hands-on experience building production applications with Python. 
• Good experience with JavaScript or TypeScript and modern application architectures. 
• Experience designing REST APIs, microservices, and distributed systems. 
• Practical understanding of LLMs, prompt engineering, RAG, embeddings, vector search, and AI application patterns. 
• Experience integrating commercial or open-source AI models into production systems. 
• Hands-on experience using AI coding assistants and code agents to accelerate development. 
• Understanding of agent orchestration concepts and Model Context Protocol (MCP). 
• Experience with AWS or Azure cloud platforms. 
• Experience with CI/CD, automated testing, code quality, and application observability. 
• Strong communication, documentation, and technical leadership skills. 

Good-to-Have Skills 

• Experience with AI orchestration frameworks such as LangGraph, CrewAI, Semantic Kernel, or similar. 
• Knowledge of FastAPI, Node.js, React, or Next.js. 
• Experience with containers and Kubernetes. 
• Exposure to AI evaluation, guardrails, and production monitoring. 
• Experience mentoring teams and driving AI adoption across engineering organizations. 

Job Title : Software Development Engineer in Test (SDET)

Experience : 2 to 5 Years

Location : Bangalore

Working Days : 5 Days/Week

Notice Period : Immediate to 15 Days

Interview Process : 1 Internal Round + 2 Client Rounds

Job Summary :

We are looking for a skilled Software Development Engineer in Test (SDET) with strong expertise in Java-based automation testing. The ideal candidate should have hands-on experience in automation frameworks, API testing, debugging, SQL, and cloud technologies while ensuring the delivery of high-quality software applications.

Mandatory Skills :

Java, Selenium, Appium, API Testing, SQL, AWS, Debugging, Cache Memory Concepts (Python is a Plus).

Key Responsibilities :

• Design, develop, and maintain automated test scripts using Java and Selenium/Appium.
• Perform API testing and validate backend services.
• Write and execute SQL queries for data validation and testing.
• Debug application issues and collaborate with development teams to resolve defects.
• Work with AWS environments for testing and deployment validation.
• Validate application performance involving cache memory mechanisms.
• Contribute to improving test automation frameworks and CI/CD processes.

Required Skills :

• Strong proficiency in Java (Mandatory).
• Hands-on experience with Selenium and Appium.
• Strong knowledge of API Testing.
• Good understanding of SQL.
• Experience with AWS.
• Excellent debugging and troubleshooting skills.
• Understanding of cache memory/caching concepts.
• Python knowledge is an added advantage.

Byteridge is seeking a Business Intelligence Solutions engineer to drive

transformative analytics and AI-powered insights for our strategic customers across India. You will lead

complex deployments of Amazon QuickSuite and related AWS analytics services, working directly with

customers to accelerate their data-driven transformation.

This role combines deep technical expertise in business intelligence, data integration, and AI automation to deliver production-ready solutions that unlock the full potential of customer data across multi-cloud environments.

What You'll Do

Solution Architecture & Deployment

• Lead end-to-end deployments of Amazon QuickSuite, QuickSight, and AWS analytics solutions forstrategic customers

• Design and implement comprehensive BI architectures that integrate with diverse data sourcesacross multi-cloud environments

• Develop custom connectors, APIs, and MCP (Model Context Protocol) integrations to extendplatform capabilities

• Configure and optimize Agents, Spaces, Topics, and Dashboards for customer-specific use cases

Technical Development & Integration

• Build custom connectors and integrations to connect QuickSuite with enterprise data sources

• Develop API-based solutions and automation workflows to streamline BI operations

• Implement data pipelines connecting multi-cloud data sources (AWS, Azure, GCP) to analyticsplatforms

• Create reusable templates, accelerators, and best practices for rapid deployment

Customer Engagement & Enablement

• Partner with customer teams to understand business requirements and translate them into

technical solutions

• Provide technical guidance on dashboard design, data modeling, and visualization best practices

• Train customer teams on QuickSuite capabilities, agent configuration, and self-service analytics

• Identify expansion opportunities and drive adoption of advanced analytics features

What We're Looking For

Core Qualifications

• Bachelor's degree in Computer Science, Data Science, Engineering, or equivalent practical

experience

• 4-6 years of experience in business intelligence, data analytics, or technical consulting roles

• Strong programming skills in Python, JavaScript, SQL, or similar languages

• Experience with BI platforms, data visualization, and analytics solution deployment

Technical Expertise (High-Level Alignment)

• Proficiency with business intelligence and data visualization tools (QuickSight, Tableau, Power BI, or

similar)

• Experience with API development, REST services, and integration patterns

• Understanding of data modeling, ETL/ELT processes, and data warehouse concepts

• Familiarity with AWS analytics services (QuickSight, Athena, Glue, Redshift) or equivalent platforms

Preferred Experience

• Hands-on experience with Amazon QuickSuite or similar AI-powered analytics platforms

• Knowledge of MCP (Model Context Protocol) and custom connector development

• Experience configuring AI agents, knowledge bases, and automated workflows

• Background working with multi-cloud data sources and hybrid architectures

• Understanding of data governance, security, and compliance requirements

Essential Attributes

• Excellent problem-solving skills with ability to navigate ambiguous requirements

• Strong communication skills to engage with technical and business stakeholders

• Ability to manage multiple customer engagements and prioritize effectively

• Customer-focused mindset with commitment to delivering measurable business outcomes

At Oracle Health, we’re building the future of healthcare

At Oracle Health, we’re building the future of healthcare—cloud-native healthcare solutions with AI at their core, designed to operate at nation-scale. Our mission is to transform how hospitals and physicians work, enabling better patient care while ensuring accurate, timely reimbursement.

We are modernizing Electronic Health Record and Clinical Analytics systems using LLMs and AI agents, helping clinicians focus more on patients and less on administrative burden.

We’re looking for highly skilled AI engineers to design and build high-scale, cloud-based data processing pipelines that ingest, transform, and analyze massive volumes of healthcare data with low latency, powering business insights and analytics across EHR and RCM systems.

You will leverage LLMs, AI agents, and modern data platforms to solve problems like clinical decision support, revenue optimization, and workflow automation while using AI-assisted development tools to accelerate delivery.

Responsibilities

Key Responsibilities

• Build and enhance data pipelines, ETL workflows, and transformations.
• Contribute to LLM/agent-based features and analytics use cases.
• Work with EHR/RCM datasets and support KPI/dashboard development.
• Learn and apply best practices in cloud, data engineering, and LLMOps.

Mandatory Qualifications

• BS/MS in Computer Science or equivalent.
• 4+ years of relevant software engineering experience.
• Strong software engineering skills in Python/Java.
• Strong knowledge of SQL.
• Deep expertise in data engineering: ETL, data transformation, data modelling (Spark, SQL), hands-on experience in BI.
• Experience building high-scale distributed data systems.
• Cloud experience (OCI/AWS/Azure).
• Experience with creating major new functionality in a software system all the way from design, through development and testing to production deployment.
• Experience with collaborating across multiple functional areas to develop components that are part of a larger system.
• Experience with LLMs, prompt engineering, and agent frameworks.
• Experience with blending hands-on coding with smart adoption of AI-driven solutions to rapidly prototype, test, iterate, and deliver reliable code.
• Experience using ChatGPT, Claude, or similar models on a routine basis to improve productivity.

Preferred Qualifications

• Experience with agentic architectures or GenAI platforms.
• Background in healthcare or digital health systems.
• Understanding of EHR systems and RCM workflows.
• Familiarity with healthcare coding standards (ICD/CPT).

We're Hiring: Gen AI Engineer (Remote)

Join VDart Digital to build cutting-edge AI solutions using Generative AI, LLMs, RAG, Agentic AI, Python, FastAPI, React.js, LangChain, and Azure AI. Apply now and be part of the future of enterprise AI

Key Responsibilities

Design and develop GenAI applications using LLMs, RAG, and Agentic AI frameworks.

Build AI agents and workflows using LangChain and LangGraph.

Develop backend APIs and AI services using Python and FastAPI.

Build AI-powered frontend experiences using React.js.

Implement RAG pipelines using vector databases and enterprise data sources.

Integrate solutions with Azure OpenAI, Azure AI Search, and Azure AI services.

Deploy and manage AI applications using Azure cloud and DevOps practices.

Required Skills

Strong experience in Generative AI, LLMs, RAG, Agentic AI.

Hands-on experience with LangChain, LangGraph, Prompt Engineering.

Strong programming skills in Python, FastAPI.

Experience with React.js development.

Experience with Azure OpenAI, Azure AI Search, Azure AI Studio / Azure ML.

Experience with Vector Databases: FAISS, Pinecone, ChromaDB, Weaviate.

Knowledge of Docker, CI/CD, APIs, and cloud-native application development.

About the Role

We are looking for a highly accomplished Generalist Fullstack Engineer for an immediate long-term track opportunity.

This is a 90% hands-on core engineering role. If you are looking for a management or guidance-only position, this is not the right fit. We need builders who love writing high-quality code and own end-to-end features across both backend services and frontend architectures.

Job Parameters & Eligibility

• Experience Required: 5 to 10 Years (Profiles with less than 5 years will not be evaluated).
• Work Mode: Hybrid (3 days Work From Office compulsory at Koramangala, Bengaluru).
• Joining Timeline: Immediate Joiners / Candidates currently serving notice with a Last Working Day (LWD) within the next 20 days only.

Key Responsibilities

• End-to-End Delivery: Design, develop, and deploy highly performant fullstack web applications.
• Backend Mastery: Build modular, scalable, and secure microservices and RESTful/GraphQL APIs.
• Frontend Engineering: Architect clean, dynamic user interfaces ensuring highly optimized state management and reusable components.
• Infrastructure & Data: Work natively with cloud infrastructures and design optimized SQL relational database systems.

Technical Stack Requirements

Backend Depth:

• Advanced hands-on experience in Node.js (Highly Preferred), Python, Java, or Golang.
• Solid experience writing optimized queries and managing relational architectures in SQL.

Frontend Depth:

• Proven UI experience working extensively with modern libraries like React.js, Angular, or Vue.js.
• Deep knowledge of complex frontend state management patterns and structural performance optimization.

Cloud & Infrastructure:

• Robust exposure to AWS core services.
• Familiarity with Infrastructure as Code (IaC) tools like Terraform is a significant plus.

What We Avoid

• Profiles with less than 5 years of absolute engineering depth.
• Frequent job hoppers with multiple short stints.
• Developers whose frontend knowledge is restricted to basic styling rather than complete end-to-end logic/state implementation.

Experience : 3 to 5 years

Required Skills :

-3+ years experience needed

-python,django framework

-Ajax, jquery, web services knowledge

-angular js would be added advantage but not compulsory

-Good knowledge of MySQL or MongoDB or Postgresql

-Added advantage if experience working with angular JS, Scrapping scripts etc

-Good english communication skill

Byteridge is seeking a Rapid Prototyping Engineer specializing in AI Infrastructure & Optimization to work with our most strategic customers on deploying, fine-tuning, and optimizing large language models at scale. You will be at the forefront of Byteridge's AI infrastructure capabilities, helping customers unlock the full potential of foundation models through expert-level deployment on GPU infrastructure.

This highly technical role requires deep expertise in machine learning infrastructure, GPU optimization, and production ML systems, combined with the ability to translate complex technical concepts into customer success.

What You'll Do

Model Deployment & Optimization

• Lead end-to-end deployments of large language models on AWS infrastructure for strategic

customers

• Design and implement training, fine-tuning, and inference pipelines using Amazon SageMaker AI

• Optimize model performance through GPU-level tuning, kernel optimization, and infrastructure

configuration

• Deploy models on diverse GPU architectures including NVIDIA and AWS custom silicon (Trainium,

Inferentia)

Infrastructure Architecture & Performance

• Architect scalable ML infrastructure using SageMaker AI Inference, HyperPod, and distributed

training frameworks

• Implement CUDA-level optimizations and custom kernels for improved model performance

• Design storage and networking architectures optimized for high-throughput ML workloads

• Troubleshoot and resolve complex performance bottlenecks at the GPU driver and kernel level

Customer Engagement & Technical Leadership

• Partner with AWS AI Specialist Solution Architects and customer ML teams to understand model

requirements and deployment constraints

• Provide technical guidance on model selection, fine-tuning strategies, and production best practices

• Conduct performance benchmarking and cost optimization analysis for ML workloads

• Share field insights with AWS product teams to influence infrastructure and service roadmaps

What We're Looking For

Core Qualifications

• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience (Master's or

PhD preferred)

• 5+ years of experience in machine learning infrastructure, model deployment, or GPU computing

• Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow, JAX)• Deep understanding of LLM architectures, training methodologies, and inference optimization

Technical Expertise (High-Level Alignment)

• Hands-on experience training, fine-tuning, or deploying large language models in production

• Proficiency with GPU programming, CUDA, and kernel-level optimization techniques

• Experience with distributed training frameworks and multi-GPU/multi-node orchestration

• Strong knowledge of AWS core services: EC2 (GPU instances), S3, EFS, VPC, and networking

Preferred Experience

• Direct experience with Amazon SageMaker AI (Training, Inference, HyperPod) or equivalent ML

platforms

• Understanding of GPU architectures (NVIDIA A100, H100) and AWS custom silicon (Trainium,

Inferentia)

• Experience with model compression techniques (quantization, pruning, distillation)

• Knowledge of MLOps practices, model monitoring, and production ML system design

• Background in high-performance computing, distributed systems, or systems programming

Essential Attributes

• Ability to dive deep into technical problems and debug complex infrastructure issues

• Strong analytical skills with data-driven approach to optimization

• Excellent communication skills to explain complex technical concepts to diverse audiences

• Comfortable working in ambiguous, fast-paced environments with evolving requirements

• Ownership mindset with ability to drive projects from architecture to production

Supercharge Your Career as a AI DevOps Engineer at Technoidentity!

At Technoidentity, we're a Data & AI product engineering company with over 15 years of expertise in building durable digital products, intelligent enterprise solutions, and scalable Data & AI platforms. As we continue expanding globally, it's the perfect time to join our team of tech innovators and make a lasting impact.

What’s in it for You?

We are looking for an AI DevOps Engineer with 0–3 years of experience who is passionate about AI, Cloud, DevOps, and Automation. The role involves building, deploying, and managing AI-powered applications, LLM solutions, and cloud-native platforms while ensuring reliability, scalability, security, and observability.

What Will You Be Doing?

• Develop and deploy AI/ML and Generative AI solutions using Python.
• Build applications leveraging LLMs, RAG, and AI agents.
• Create and maintain CI/CD pipelines for AI applications.
• Deploy and manage workloads using Docker and Kubernetes.
• Support cloud platforms (AWS, Azure, or GCP).
• Implement Infrastructure as Code (Terraform) and automation workflows.
• Monitor applications using observability tools such as Prometheus, Grafana, and logging platforms.
• Collaborate with engineering teams to ensure system reliability, performance, and security.
• Contribute to MLOps practices, AI accelerators, and reusable frameworks.

Requirements

What Makes You the Perfect Fit?

• Python programming (mandatory)
• Understanding of Machine Learning, LLMs, Prompt Engineering, and RAG
• Experience with OpenAI, LangChain, LlamaIndex, or Hugging Face
• Docker, Kubernetes, Git, and CI/CD tools
• AWS, Azure, or GCP
• PostgreSQL; MongoDB and Vector Databases are a plus
• Basic knowledge of MLOps, Terraform, and workflow orchestration tools (Airflow/Temporal)
• Familiarity with observability and monitoring tools

Qualifications

• Bachelor's degree in Computer Science, AI, Data Science, IT, or related field
• 0–3 years of experience in AI/ML, Software Engineering, Cloud, DevOps, or related areas

Nice to Have

• Experience with Agentic AI frameworks
• Knowledge of MLOps and AI platform operations
• Exposure to enterprise-grade monitoring, reliability engineering, and security best practices

About Indee

Indee is a secure video streaming and distribution platform trusted by the world's largest studios, streamers, and awards bodies. Today more than 1100 companies use Indee to power screeners, awards campaigns, content sales, and secure review workflows, including partners such as Netflix, A24 Films, Amazon MGM Studios, Disney, Paramount Pictures, Universal Pictures, NBC Universal, Focus Features, Paramount Global, Neon, STARZ, and Magnolia Pictures. Indee has achieved consistent growth, averaging 60% year-on-year growth over the past five years.

About the role

We are seeking a QA Manager with 8-12 years of experience in software testing and quality assurance, including experience leading QA teams in fast-paced product environments. The ideal candidate is a hands-on quality leader with strong expertise in both manual and automation testing, a proven track record of driving high-velocity daily releases, and the ability to build and develop high-performing QA teams. This individual will be responsible for the quality strategy for Indee's products while actively contributing to release planning, testing initiatives, process improvements, automation efforts, and production quality outcomes.

Responsibilities

• Own and continuously evolve Indee's QA strategy across manual, automation, regression, exploratory, API, performance, and release testing.
• Lead QA efforts throughout the software development lifecycle, including test planning, test execution, defect management, risk assessment, release validation, and release sign-offs.
• Drive adoption of AI-enabled testing approaches and continuously evaluate opportunities to improve testing efficiency, quality, and coverage.
• Drive release quality by establishing strong validation processes, improving regression coverage, and minimizing production defects.
• Define, track, and report on key quality metrics, including production defect leakage, release readiness, automation coverage, defect trends, and test effectiveness.
• Conduct root cause analysis for production issues and implement preventive actions to improve product quality and release stability.
• Drive automation initiatives across the QA function, improving automation coverage, framework reliability, execution efficiency, and long-term maintainability.
• Partner with engineering teams to identify automation opportunities and improve testing effectiveness through API-based and UI-based automation approaches
• Mentor and develop QA engineers across manual and automation testing disciplines, supporting skill development, career growth, and technical excellence.
• Enable manual QA engineers to contribute to automation efforts through coaching, structured ownership, and ongoing support.
• Collaborate with product and engineering teams to drive quality throughout the software development lifecycle, from requirements and design through testing, release, and production support.
• Support timely investigation, validation, and resolution of customer-reported issues, production incidents, and QA-related escalations.
• Improve release planning, workload allocation, and team capacity management to support multiple concurrent projects and business priorities.
• Lead, mentor, and manage the QA team, including hiring, onboarding, performance management, capacity planning, and succession planning.
• Foster a collaborative, accountable, and high-performing team culture that promotes ownership, continuous improvement, and operational excellence.

Requirements

Education: Bachelor's degree in computer science, software engineering, or a related field; master's degree preferred.

Experience:

• 8-12 years of QA experience in product companies.
• 4+ years of experience managing/leading QA teams.

Must Haves

• Strong people leadership and planning skills
• Ability to schedule work within defined timelines for the team.
• Strong hands-on experience in QA of web and mobile applications.
• Experience in test automation using Selenium with Python, leveraging BDD frameworks.
• Experience with API testing using tools like Postman or equivalent.
• Strong understanding of test strategy, test planning, regression testing, defect management, and release validation processes.
• Experience leading QA for production releases and driving release sign-off decisions.
• Experience defining, tracking, and analyzing quality metrics and release health indicators.
• Strong understanding of root cause analysis and defect prevention methodologies.
• Experience working in Agile/Scrum environments.
• Strong stakeholder management, communication, and cross-functional collaboration skills.
• Strong capabilities in git/github
• Strong experience in JIRA, issue tracking, JIRA customization and reporting.
• Experience with Appium or mobile automation frameworks.

Good-to-haves

• Exposure to performance testing
• Understanding of ISO-27001 processes and frameworks
• Understanding of SOC-2 compliance and application / QA-specific needs.
• Exposure to security and penetration testing.
• Strong background in CI/CD pipelines

Benefits

• Competitive salary and comprehensive benefits package.
• Opportunity to work with cutting-edge technologies and industry-leading experts.
• Flexible work environment with the option for remote work for 3 weeks a month (hybrid).
• Professional development opportunities and support for continued learning.
• Dynamic and collaborative company culture with opportunities for growth and advancement.

If you are passionate about software quality and leading high-performing teams, value collaboration, and are eager to work in a respectful environment, we'd love to hear from you!

Principal DevOps Engineer

Note - Screening Requirement: Please note that this position requires a minimum of 8+ years of hands-on Architecting DevOps/SRE/Platform Engineering experience specializing in AWS, EKS/Kubernetes, Terraform, Python, Jenkins, and AI workflows (Mandatory skills) from scratch.

We are looking for an absolute builder who has a proven track record of personally architecting, designing and setting up production-grade AWS EKS clusters entirely from scratch. If your experience is primarily limited to managing, maintaining, or optimizing pre-existing environments that were already stood up by another team, this is not the right opportunity for you.

Who are we?

Securin is an AI-driven cybersecurity company focused on proactive, adversarial exposure and vulnerability management. Our mission is to help organizations reduce cyber risk by identifying, prioritising, and remediating the issues that matter most. Powered by a seasoned team of threat researchers and status as a Certified Naming Authority (CNA), Securin combines artificial intelligence / machine learning, threat intelligence, and deep vulnerability research (including the Dark Web) to deliver an adversarial approach to cyber defense. We help enterprises shift from reactive patching to strategic, risk-based exposure and vulnerability management – driving smarter security decisions and faster remediation.

What do we promise?

We are a highly effective tech-enabled cybersecurity solutions provider and promise continual security posture improvement, enhanced attack surface visibility, and proactive prioritized remediation for every one of our client businesses.

What do we provide?

● A chance to be on the leading edge of cybersecurity and AI

● Ability to have direct impact on company growth and revenue strategy

● An opportunity to mentor and be mentored by experts in multiple disciplines

What do we deliver?

Securin helps organizations to identify and remediate the most dangerous exposures, vulnerabilities, and risks in their environment. We deliver predictive and definitive intelligence and facilitate proactive remediation to help organizations stay a step ahead of attackers. By utilising our cybersecurity solutions, our clients can have a proactive and holistic view of their security posture and protect their assets from even the most advanced and dynamic attacks.

Securin has been recognized by national and international organizations for its role in accelerating innovation in offensive and proactive security. Our combination of domain expertise, cutting-edge technology, and advanced tech-enabled cybersecurity solutions has made Securin a leader in the industry.

Core Technology Stack

AWS , EKS / Kubernetes, Jenkins , Python ,Terraform ,CI/CD , AI

Key Responsibilities:

● Architect and manage the end-to-end SaaS platform infrastructure on AWS, including EKS cluster design, VPC networking, IAM, and multi-region availability.

● Build, maintain, and optimize Jenkins-based CI/CD pipelines and develop Python automation scripts for provisioning, deployments, and runbook automation.

● Define and enforce platform SLOs/SLAs; own the observability strategy across logging, metrics, and tracing.

● Manage and participate in the on-call rotation; act as escalation point for P1/P2 incidents and drive post-incident reviews.

● Drive Infrastructure-as-Code (IaC) practices with Terraform/CloudFormation and champions a culture of automation and operational excellence.

● Collaborate cross-functionally with product, security, and engineering teams to align infrastructure roadmap with business goals.

● Identify opportunities to leverage AI to automate operational and DevOps workflows.

● Design and implement AI-assisted solutions for incident triaging, root cause analysis, log analysis, and performance optimization.

● Drive the adoption of AI-powered tools for infrastructure management, deployment automation, monitoring, and troubleshooting.

● Build intelligent workflows that reduce manual effort in release management, capacity planning, and operational support.

● Integrate AI capabilities into CI/CD pipelines to improve code quality, deployment reliability, and operational efficiency.

● Collaborate with engineering teams to automate repetitive tasks and improve developer productivity.

● Define best practices and governance for the safe and effective use of AI across DevOps processes.

● Measure and report on productivity gains, operational improvements, and cost savings achieved through AI adoption.

Requirements:

● 8+ years of experience in DevOps, SRE, or cloud infrastructure engineering roles.

● Deep hands-on expertise with AWS services (EC2, EKS, RDS, S3, IAM, VPC, CloudFront, Route53, Lambda, etc).

● Strong Kubernetes experience: cluster management, Helm, autoscaling (HPA/KEDA).

● Proficiency with Jenkins for complex CI/CD pipeline design and maintenance.

● Solid Python scripting skills for automation, tooling, and infrastructure management tasks.

● Experience with Infrastructure-as-Code using Terraform and/or AWS Cloud Formation.

● Proven track record of architecting and managing end-to-end SaaS products in a cloud-native environment.

● Strong understanding of networking fundamentals, security best practices, and compliance frameworks (SOC 2, ISO 27001 a plus).

● Hands-on experience with on-call processes and incident management frameworks.

Preferred Qualifications:

● AWS certifications: Solutions Architect Professional, DevOps Engineer Professional, or equivalent.

● Familiarity with service mesh, secrets management (Vault, AWS Secrets Manager), and zero-trust security models.

● Experience with multi-tenant SaaS architectures and tenant isolation strategies.

● Knowledge of FinOps principles and AWS cost management tooling.

● Experience with database DevOps: RDS, Aurora schema migrations, and backup strategies.

Core Competencies:

● Strategic Thinking – ability to translate business goals into scalable technical architecture.

● Operational Excellence – strong bias for reliability, automation, and continuous improvement.

● Communication – ability to clearly articulate complex technical topics to non-technical stakeholders.

● Ownership Mindset – proactively identifies and resolves risks without waiting to be asked.

● Resilience Under Pressure – calm and decisive during incidents; leads by example in high-stress situations.

Why should we connect?

We are a bunch of passionate cybersecurity professionals who are building a culture of security. Today, cybersecurity is no more a luxury but a necessity with a global market value of $150 billion.

At Securin, we live by a people-first approach. We firmly believe that our employees should enjoy what they do. For our employees, we provide a hybrid work environment with competitive best-in-industry pay, while providing them with an environment to learn, thrive, and grow. Our hybrid working environment allows employees to work from the comfort of their homes or the office if they choose to. For the right candidate, this will feel like your second home.

If you are passionate about cybersecurity just as we are, we would love to connect and share ideas

SOLARSQUARE  ·  ENGINEERING

Staff Engineer, Data Platform

Team: Data Engineering    ·    Level: Staff (Individual Contributor)    ·    Experience: 8+ years      ·    Full-time

Own the data platform that turns every customer and field interaction into a decision SolarSquare can act on.

About SolarSquare :

At SolarSquare we are building the Home-Energy brand of future India. We help homes switch to rooftop solar and move away from traditional coal electricity. We are a full-stack D2C residential solar brand — designing, installing, maintaining (after-sales), and financing solar systems for home-owners across India.

In a few short years we have scaled to become the leading residential solar brand in India. We are obsessed with quality, customer service, and innovating to make it simple for homes to switch to solar. We are looking for leaders to join us in this mission.

Get to know us

• SolarSquare - company website
• Featured by TIME as one of the World’s Top GreenTech Companies of 2025
• SolarSquare raises $53M Series C led by B Capital (Moneycontrol)
• India’s rooftop solar market and SolarSquare’s growth (TechCrunch)

About the role :

As a Staff Engineer on Data Platform, you set the technical direction for how we move, model, and serve data across the entire customer lifecycle — from real-time operational streams off thousands of field devices to the analytical layer our leaders and AI systems depend on. You operate at the scope of the platform: ambiguous problems land on your desk, and you turn them into systems the whole org builds on.

What you’ll own :

• Design and scale the data platform end to end: streaming ingestion, batch pipelines, the analytical warehouse, and a governed self-serve metrics layer.
• Build real-time operational data streams that power field operations and customer-facing experiences with low latency and high reliability.
• Own data quality, lineage, and governance — including PII handling — so teams trust the data and never dump it mindlessly.
• Define a golden metrics layer and the standards, contracts, and tooling that make analytics self-serve across the org.
• Set the bar on craft: review designs, clear data tech debt every sprint, and mentor engineers across pods.

The Tech you’ll work with :

You’ll work across event streaming (Kafka), PostgreSQL as the system of record, a columnar analytical warehouse for OLAP, Python-based pipelines, and Metabase for self-serve BI — with more workloads moving to real-time and columnar storage as we scale. We’re stack-agnostic for the right person; fundamentals matter more than any one tool.

What we’re looking for :

• 8+ years building large-scale data systems in production, with deep ownership of at least one major data platform.
• Strong command of distributed data processing and streaming architectures, plus modern columnar / analytical warehouses.
• Expert SQL and data modeling; fluency in data quality, lineage, and governance.
• Proven ability to turn ambiguous business questions into durable data models and reusable platform abstractions.
• Experience setting technical direction and growing the engineers around you.
• Customer-obsessed and impact-led: you start from the customer’s pain and judge yourself by the metric your work moves, not the tickets you close.
• High agency: you don’t wait to be told — you spot problems, pick them up, and own the outcome through to production.
• Craft over shortcuts: you fix root causes rather than symptoms, clear tech debt as you go, and don’t ship bugs.
• Bias for speed and simplicity: you build once for reuse, automate the mundane, and let AI draft the first pass so your judgment goes where it matters.
• Data-driven: you reach for evidence over assumptions and let results guide the next decision.

Bonus points

• Experience with lakehouse architectures, real-time analytics, or geospatial / IoT-scale data.
• Exposure to semantic layers and self-serve analytics platforms.
• Built data platforms that feed ML or AI systems.

Why you’ll love building here

• Direct ownership of high-impact initiatives with visible customer and business outcomes.
• An AI-native engineering culture with first-class tooling and internal agents.
• A high-agency, low-bureaucracy environment where you debate what’s right and ship.
• A meritocracy where growth and recognition track impact, not tenure.
• Competitive compensation.
• A front-row seat to putting clean energy on millions of Indian rooftops.