21 Artificial Intelligence (AI) Jobs in Coimbatore | Artificial Intelligence (AI) Job openings in Coimbatore

TECHJAYS

THE AI REIMAGINATION COMPANY

Position DevOps Lead

Experience 10+ Years

Location Coimbatore / Hybrid

Joining Immediate / ASAP

Primary SkillsDevOps, AWS or Azure, CI/CD, Kubernetes, Docker, Terraform, Linux, Git, Cloud Infrastructure, Infrastructure Automation, Monitoring & Observability

Preferred SkillsAI/ML Infrastructure Exposure, GenAI Applications, GitOps, Argo CD, Prometheus, Grafana, Python, Bash, PowerShell, Cloud Security, FinOps

About Techjays

At Techjays, we're helping businesses reimagine how they build, operate, and scale with AI at the core. We focus on developing secure, scalable, production-grade AI systems that solve complex business challenges and deliver measurable business outcomes.

Our team brings together experienced engineers and technology leaders from organizations such as Google, NetApp, ADP, Cognizant Consulting, and Capgemini. We work with global clients to build advanced AI-powered applications, enterprise platforms, and intelligent automation solutions.

We're looking for a DevOps Lead who can take ownership of cloud infrastructure, deployment automation, CI/CD pipelines, platform reliability, and engineering operations.

The ideal candidate will have deep hands-on expertise in either AWS or Azure, along with strong experience in Kubernetes, containerization, Infrastructure as Code, and production cloud environments.

You will lead the design and implementation of reliable infrastructure platforms, establish DevOps best practices, and work closely with software engineering and AI teams to support the deployment and operation of modern applications.

This role requires a strong hands-on cloud and DevOps specialist who can architect, implement, troubleshoot, and optimize production infrastructure. Prior exposure to AI/ML or AI-enabled applications is required, but specialized MLOps expertise is not mandatory.

Key Responsibilities

1. Cloud Infrastructure & Architecture

• Lead the design, implementation, and management of scalable, secure, and highly available cloud infrastructure.
• Own cloud infrastructure architecture and operations across AWS or Azure.
• Design and manage cloud environments covering compute, networking, storage, databases, and container platforms.
• Establish infrastructure standards, architecture patterns, and operational best practices.
• Manage cloud resource provisioning, configuration, scaling, and environment management.
• Ensure infrastructure meets requirements for availability, performance, security, and reliability.
• Drive infrastructure improvements through automation and continuous optimization.

2. DevOps & CI/CD Engineering

• Design, implement, and maintain CI/CD pipelines for application development and deployment.
• Manage multi-stage deployment workflows across development, testing, staging, and production environments.
• Implement automated build, testing, deployment, and release processes.
• Establish reusable pipeline templates, deployment standards, and approval workflows.
• Manage deployment strategies, including rolling, blue/green, and canary deployments.
• Implement rollback mechanisms and ensure reliable production releases.
• Integrate CI/CD workflows with source control, artifact repositories, and container registries.
• Continuously improve deployment efficiency, release reliability, and engineering productivity.

3. Containerization & Kubernetes Management

• Architect and manage containerized application environments using Docker and Kubernetes.
• Manage production Kubernetes clusters using Amazon EKS or Azure AKS.
• Implement Kubernetes configurations covering deployments, services, networking, secrets, storage, and resource management.
• Work with Helm charts for application packaging and deployment.
• Optimize container resource utilization, application scaling, and cluster performance.
• Troubleshoot complex container and Kubernetes-related production issues.
• Establish best practices for container security and workload reliability.

4. Infrastructure as Code & Automation

• Implement Infrastructure as Code using Terraform and cloud-native provisioning tools.
• Automate infrastructure provisioning, configuration management, and environment setup.
• Develop reusable infrastructure modules and deployment automation workflows.
• Use Python, Bash, or PowerShell to automate operational tasks and improve efficiency.
• Reduce manual intervention through standardization and automation.
• Maintain infrastructure documentation, configuration standards, and version-controlled deployment workflows.

5. Monitoring, Reliability & Production Operations

• Establish centralized monitoring, logging, alerting, and observability across cloud environments.
• Implement monitoring solutions using CloudWatch, Azure Monitor, Prometheus, Grafana, or equivalent platforms.
• Monitor application availability, infrastructure health, resource utilization, and system performance.
• Lead troubleshooting and resolution of complex production incidents.
• Conduct root cause analysis and implement permanent corrective actions.
• Establish operational practices for backup, disaster recovery, availability, and business continuity.
• Improve system reliability through proactive monitoring and performance optimization.

6. Cloud Security & Governance

• Implement cloud security best practices across infrastructure and application environments.
• Manage IAM, RBAC, access controls, service identities, and secrets management.
• Secure cloud networking, virtual networks, firewalls, and infrastructure access.
• Implement container security and infrastructure hardening practices.
• Ensure cloud environments follow organizational security and compliance requirements.
• Identify infrastructure vulnerabilities and coordinate remediation activities.
• Establish secure deployment and configuration management practices.

7. AI Infrastructure & Engineering Collaboration

• Work closely with AI/ML and software engineering teams to provide infrastructure for AI-powered applications.
• Support the deployment and operation of LLM-based applications, AI services, and AI-enabled platforms.
• Design cloud infrastructure capable of supporting AI workloads, including compute, storage, networking, and containerized services.
• Support the infrastructure requirements of AI applications across development, testing, and production environments.
• Collaborate with engineering teams to improve deployment reliability, scalability, and operational performance of AI-powered systems.
• Evaluate infrastructure technologies and tools that support evolving AI application requirements.

8. Technical Leadership & Team Development

• Provide technical leadership to DevOps engineers and guide implementation across projects.
• Establish engineering standards, infrastructure best practices, and operational procedures.
• Mentor team members on cloud architecture, automation, CI/CD, Kubernetes, and production operations.
• Lead technical discussions and make architecture decisions involving infrastructure and DevOps technologies.
• Collaborate with engineering, security, and product teams to align infrastructure capabilities with business requirements.
• Drive continuous improvement across DevOps processes, tools, and engineering practices.

Required Technical Skills & Experience

1. Cloud Platforms

• 10+ years of overall experience in DevOps, cloud infrastructure, or platform engineering.
• Strong hands-on expertise in at least one major cloud platform: AWS or Azure.
• Practical experience designing, deploying, and operating production-grade cloud infrastructure.

AWS: EC2, S3, IAM, VPC, EKS, Lambda, ECR, CloudWatch, and related infrastructure services.

Azure: Azure Virtual Machines, VNets, AKS, Azure DevOps, Azure Container Registry, Azure Monitor, Key Vault, and related infrastructure services.

Candidates do not need to be experts in both AWS and Azure. Deep expertise in either platform is the priority.

2. DevOps & CI/CD

• Strong experience designing and maintaining CI/CD pipelines.
• Hands-on experience with Azure DevOps, Jenkins, GitHub Actions, GitLab CI, or equivalent tools.
• Understanding of multi-stage pipelines, automated deployments, release approvals, and artifact management.
• Experience implementing deployment automation and rollback strategies.
• Strong understanding of Git workflows and version control practices.

3. Containers & Kubernetes

• Strong hands-on experience with Docker and Kubernetes.
• Practical experience managing EKS or AKS environments.
• Understanding of Kubernetes networking, scaling, storage, secrets, and workload management.
• Experience with Helm and container orchestration.
• Ability to troubleshoot production container and Kubernetes environments.

4. Infrastructure as Code & Scripting

• Strong experience with Terraform and Infrastructure as Code practices.
• Familiarity with CloudFormation, Bicep, ARM templates, or similar tools.
• Working knowledge of Python, Bash, or PowerShell for infrastructure automation.
• Strong understanding of Linux administration and system troubleshooting.

5. Monitoring & Reliability Engineering

• Experience implementing infrastructure and application monitoring.
• Familiarity with CloudWatch, Azure Monitor, Prometheus, Grafana, and centralized logging solutions.
• Understanding of incident management, root cause analysis, performance optimization, and system availability.
• Experience establishing alerting, operational dashboards, and reliability practices.

6. AI/ML Infrastructure Exposure

• Prior experience supporting AI/ML applications, Generative AI platforms, LLM applications, or AI-enabled products.
• Understanding of infrastructure requirements for deploying and operating AI-powered applications.
• Familiarity with containerized AI services, cloud-based model integrations, and scalable application environments.

Note: This role does not require specialized MLOps expertise or model development experience. Strong cloud and DevOps engineering fundamentals remain the primary requirement.

Preferred Skills

• Experience implementing GitOps workflows using Argo CD or similar tools.
• Experience with blue/green deployments, canary releases, and automated rollback mechanisms.
• Exposure to cloud security, enterprise networking, governance, and landing-zone architecture.
• Experience with cloud cost optimization and FinOps practices.
• Familiarity with AI/ML infrastructure and production GenAI applications.
• Experience with Python-based automation and infrastructure tooling.
• Relevant AWS, Azure, Kubernetes, or Terraform certifications.

What We're Looking For Beyond Skills

• Cloud Expertise: Deep technical specialization in AWS or Azure, with the ability to design and manage production infrastructure independently.
• Hands-on Engineering: Someone who actively builds, automates, troubleshoots, and improves infrastructure rather than focusing only on team management.
• Technical Ownership: Takes responsibility for infrastructure reliability, deployment quality, security, and operational performance.
• System Thinking: Understands how cloud infrastructure, applications, networking, databases, and deployment pipelines work together.
• Problem-Solving: Ability to diagnose complex production issues and implement long-term engineering solutions.
• Automation Mindset: Continuously identifies opportunities to eliminate manual work and improve operational efficiency.
• Technical Leadership: Can mentor engineers, establish best practices, and drive technical decisions.
• AI Readiness: Has practical exposure to supporting AI-powered applications and understands their infrastructure requirements.
• Collaboration: Works effectively with software engineering, AI/ML, security, and product teams.

Typical Technology Environment

AreaTechnologiesCloud PlatformsAWS, AzureCI/CDAzure DevOps, GitHub Actions, Jenkins, GitLab CIContainersDocker, Kubernetes, EKS, AKS, HelmInfrastructure as CodeTerraform, CloudFormation, Bicep, ARMGitOpsArgo CD, Git-based deployment workflowsMonitoring & ObservabilityCloudWatch, Azure Monitor, Prometheus, GrafanaAutomationPython, Bash, PowerShellOperating SystemsLinux, WindowsSecurityIAM, RBAC, Secrets Management, Network SecurityAI ExposureAI/ML Applications, GenAI, LLM Platforms, AI-enabled Products

What We Offer

• Competitive compensation aligned with experience and expertise.
• Coimbatore office-based work environment with hybrid flexibility.
• Opportunity to lead cloud infrastructure and DevOps engineering for global clients.
• Exposure to modern AWS/Azure, Kubernetes, automation, and AI engineering practices.
• Paid holidays and flexible time off.
• Medical insurance covering self and family, up to ₹4 lakh per person.
• Opportunities to influence infrastructure architecture and engineering practices.
• A culture that values clarity, integrity, ownership, and continuous growth.

Join Techjays

If you're passionate about building reliable cloud platforms, automating complex infrastructure, and leading DevOps engineering for modern AI-powered applications, we'd love to hear from you.

TECHJAYS

THE AI REIMAGINATION COMPANY

AI Quality Engineer

Position : AI Quality Engineer

Experience : 3–10 Years

Location : Coimbatore / Hybrid

Joining : Immediate / Within 30 Days

Primary SkillsManual & Functional Testing, AI/ML Application Testing, LLM Testing, Prompt Testing, Test Case Design, API Testing, Regression Testing, Defect Management

Preferred SkillsRAG Testing, Chatbot Testing, AI Response Evaluation, Selenium, Playwright, Cypress, Python, JavaScript, SQL, Postman, JIRA, BDD

About Techjays

At Techjays, we're helping businesses reimagine how they build, operate, and scale with AI at the core. We focus on developing intelligent, scalable, and production-grade AI solutions that solve real-world business challenges.

Our global team brings together experienced technology professionals from organizations such as Google, NetApp, ADP, Cognizant Consulting, and Capgemini. We work with global clients to build AI-powered applications, intelligent automation platforms, and enterprise software solutions.

We're looking for an AI Quality Engineer with strong functional testing expertise and prior hands-on experience testing AI/ML-powered applications.

This role goes beyond traditional software testing. You will be responsible for validating the quality, accuracy, reliability, and behaviour of AI-powered features, ensuring that intelligent applications perform consistently across different scenarios and real-world use cases.

The ideal candidate should understand both traditional QA methodologies and the unique testing challenges associated with AI systems, including non-deterministic outputs, prompt behaviour, hallucinations, response relevance, and edge-case validation.

Prior hands-on experience testing AI/ML-based products or applications is mandatory. Candidates with only traditional manual testing experience and no AI project exposure will not be a fit.

Key Responsibilities

1. AI Application & LLM Testing

• Perform functional and quality testing of AI-powered applications, LLM-based products, chatbots, and intelligent automation systems.
• Design test scenarios to validate AI-generated responses for accuracy, relevance, consistency, completeness, and contextual understanding.
• Test prompts, prompt variations, and conversational flows to identify unexpected outputs and behavioural inconsistencies.
• Evaluate AI responses for hallucinations, incorrect information, irrelevant answers, and context retention issues.
• Validate AI application behaviour across different user inputs, edge cases, and complex scenarios.
• Test RAG-based applications by validating document retrieval, response relevance, contextual accuracy, and source grounding.
• Evaluate AI-powered search, recommendation engines, and other intelligent product features.
• Collaborate with AI engineers and data science teams to define acceptance criteria and quality benchmarks.

2. Functional & Manual Testing

• Analyse business and technical requirements and convert them into comprehensive test scenarios and test cases.
• Execute functional, regression, integration, system, and user acceptance testing across web and mobile applications.
• Validate end-to-end application workflows, business logic, user interactions, and data processing.
• Identify functional gaps, unexpected behaviour, and usability issues.
• Perform exploratory testing to uncover defects that may not be covered by predefined test cases.
• Ensure application functionality remains stable across different releases and environments.
• Review requirements early in the development lifecycle to identify potential quality risks.

3. AI Quality Evaluation & Validation

• Develop structured testing approaches for non-deterministic AI outputs using behaviour-based, range-based, and scenario-based validation.
• Evaluate AI response quality against expected outcomes and predefined acceptance criteria.
• Validate prompt sensitivity, context handling, conversation memory, and multi-turn interactions.
• Identify failure patterns involving hallucinations, prompt injection, incorrect retrieval, and inconsistent responses.
• Test AI system performance across different input formats, languages, and user scenarios where applicable.
• Maintain test datasets and evaluation scenarios for repeatable AI quality assessment.
• Work with engineering teams to identify root causes of AI-related defects and verify fixes.

4. API & Integration Testing

• Perform manual API testing using Postman or similar tools.
• Validate API request and response structures, status codes, authentication, authorization, and error handling.
• Test integrations between AI services, backend systems, databases, and external APIs.
• Validate data flow between application components and identify integration issues.
• Test API behaviour under different input conditions, including invalid inputs and boundary cases.
• Verify API responses and ensure consistency between frontend and backend functionality.

5. Defect Management & Quality Reporting

• Identify, document, track, and manage defects throughout the testing lifecycle.
• Maintain detailed test cases, test execution reports, defect logs, and test documentation.
• Collaborate with developers to reproduce issues, analyse root causes, and validate fixes.
• Track test coverage, defect trends, and application quality metrics.
• Communicate release risks, unresolved defects, and testing status to relevant stakeholders.
• Participate in release readiness reviews and provide quality sign-off for assigned modules.

6. Automation & Continuous Improvement

• Identify repetitive test scenarios that can be automated to improve testing efficiency.
• Support automation initiatives using Selenium, Playwright, or Cypress.
• Work with developers to improve testability and integrate testing practices into CI/CD workflows.
• Explore AI-assisted testing tools and approaches to improve test coverage and efficiency.
• Continuously improve testing methodologies for both conventional software applications and AI-powered systems.

Required Skills & Experience

1. Functional & Manual QA

• 3–5 years of hands-on experience in manual and functional software testing.
• Strong understanding of software testing methodologies, SDLC, STLC, and defect management.
• Experience designing and executing test cases for functional, regression, integration, and end-to-end testing.
• Strong knowledge of Agile/Scrum methodologies and sprint-based QA processes.
• Experience testing web applications, APIs, and mobile applications.
• Ability to analyse requirements and identify functional gaps, edge cases, and potential risks.

2. Mandatory AI/ML Testing Experience

• Prior hands-on experience testing AI/ML-powered applications or products.
• Practical experience testing LLM-based applications, AI chatbots, conversational systems, or intelligent automation features.
• Understanding of prompt testing and evaluating AI-generated responses.
• Ability to validate AI outputs for accuracy, relevance, consistency, and contextual correctness.
• Experience identifying hallucinations, unexpected AI behaviour, and response-quality issues.
• Understanding of AI application workflows, model outputs, and the challenges associated with non-deterministic systems.
• Experience collaborating with AI/ML engineers or data science teams during testing and validation.

3. API & Integration Testing

• Hands-on experience with manual API testing using Postman.
• Understanding of REST APIs, JSON, request/response validation, authentication, and error handling.
• Experience validating integrations between frontend, backend, and external services.
• Basic understanding of database validation and SQL queries.

4. Testing Tools & Technologies

• Experience with JIRA and Confluence for defect tracking and test documentation.
• Familiarity with Postman, SQL, and browser developer tools.
• Understanding of test management and reporting practices.
• Basic knowledge of BDD frameworks such as Cucumber/Gherkin is an advantage.

Preferred Skills

• Experience testing RAG-based applications, including document retrieval and contextual response validation.
• Exposure to vector databases and semantic search testing.
• Familiarity with LangChain, LangGraph, LlamaIndex, or similar AI frameworks.
• Understanding of LLM evaluation frameworks and AI quality assessment methodologies.
• Experience with AI evaluation tools such as Ragas, DeepEval, or similar frameworks.
• Exposure to prompt injection, adversarial testing, and responsible AI validation.
• Working knowledge of Selenium, Playwright, or Cypress.
• Basic scripting knowledge in Python or JavaScript.
• Familiarity with CI/CD pipelines and automated testing practices.
• Exposure to cross-browser testing tools such as BrowserStack or Sauce Labs.

What We're Looking For Beyond Skills

• AI Testing Mindset: Understands that testing AI applications requires more than checking whether a feature works. Can evaluate response quality, accuracy, relevance, and behaviour.
• Analytical Thinking: Ability to identify unusual scenarios, inconsistent outputs, and hidden quality issues.
• Strong QA Fundamentals: Applies structured testing methodologies while adapting them to AI-powered applications.
• Attention to Detail: Documents defects clearly and identifies patterns in application and AI behaviour.
• Ownership: Takes responsibility for testing quality from requirement analysis through release validation.
• Collaboration: Works effectively with developers, AI engineers, product managers, and data science teams.
• Continuous Learning: Interested in exploring emerging AI technologies and evolving testing methodologies.
• Communication: Clearly communicates test results, defect impact, quality risks, and release readiness.

What We Offer

• Competitive compensation aligned with experience and expertise.
• Flexible work environment (Coimbatore office / Hybrid).
• Paid holidays and flexible time off.
• Medical insurance covering self and family, up to ₹4 lakh per person.
• Opportunity to work on real-world AI-powered products and enterprise applications.
• Hands-on exposure to LLMs, RAG systems, agentic AI, and modern AI engineering practices.
• Opportunities to develop expertise in AI quality engineering and automation testing.
• A collaborative, multicultural environment with opportunities for professional growth.
• A culture that values clarity, integrity, ownership, and continuous learning.

Join Techjays

If you're passionate about software quality and have hands-on experience validating AI-powered applications, we'd love to hear from you.

Join us in building reliable, intelligent, and production-ready AI systems.

AI Engineer

Experience: 2–4 Years

Employment Type: Full-Time

Work Mode: Coimbatore / Hybrid

About Techjays

Techjays is an AI Reimagination Company focused on building intelligent, scalable, and impactful software solutions. We help businesses solve complex challenges through AI, automation, and modern software engineering.

We are looking for an AI Engineer who is passionate about building AI-powered applications and integrating modern AI technologies into real-world products.

Key Responsibilities

• Design, develop, and deploy AI-powered applications using Python and modern AI frameworks.
• Build and implement LLM-based applications, including Retrieval-Augmented Generation (RAG) systems.
• Work with LLM APIs such as OpenAI, Gemini, and Anthropic.
• Develop AI agents and workflows using frameworks such as LangChain and LangGraph.
• Integrate vector databases and implement efficient embedding and semantic search solutions.
• Develop scalable backend services and REST APIs.
• Work with databases, data processing pipelines, and cloud-based services.
• Collaborate with frontend and backend teams to integrate AI capabilities into applications.
• Evaluate AI model performance, improve response accuracy, and optimize application performance.
• Debug, test, and maintain production-grade AI applications.

Required Skills

• 2–4 years of experience in software development, AI engineering, or a related field.
• Strong programming knowledge in Python.
• Hands-on experience with LLMs and Generative AI applications.
• Understanding of RAG architecture, embeddings, and semantic search.
• Experience with frameworks such as LangChain, LangGraph, or LlamaIndex.
• Knowledge of vector databases such as Pinecone, FAISS, ChromaDB, or Qdrant.
• Experience in building REST APIs using FastAPI or Flask.
• Good understanding of SQL and NoSQL databases.
• Familiarity with Git, Docker, and basic cloud services.
• Strong problem-solving and analytical skills.

Good to Have

• Experience building AI agents and multi-agent systems.
• Knowledge of React or other frontend frameworks.
• Exposure to AWS, Azure, or GCP.
• Understanding of model evaluation, prompt engineering, and fine-tuning.
• Experience deploying AI applications in production environments.

What We’re Looking For

• Someone who enjoys solving real-world problems using AI.
• Ability to take ownership of tasks and deliver solutions independently.
• Strong learning mindset and willingness to explore emerging AI technologies.
• Good communication and collaboration skills.

AI Solution Architect

Experience: 12+ Years

Location: Coimbatore / Hybrid

Joining: Immediate / Within 30 Days

Primary Skills: Enterprise Architecture, Python, REST APIs, Microservices, Distributed Systems, Cloud (AWS/Azure/GCP), CI/CD, Docker, Kubernetes, Enterprise Data Architecture, Integration Patterns.

Preferred Skills: LLM Integrations, RAG Pipelines, AI Agents, Agentic Workflows, MCP (Model Context Protocol), Vector Databases, Prompt Engineering, LangChain/LlamaIndex, LLMOps, Multi-Agent Orchestration.

About the Role

At Techjays, we're helping companies reimagine how they build, operate, and scale with AI at the core. We focus on building secure, scalable, production-grade AI systems that solve real business problems and deliver measurable outcomes.

We're looking for an AI Solution Architect who can own enterprise-level solution architecture end-to-end. The ideal candidate combines deep technical expertise with the ability to understand complex business challenges, engage with prospective clients, and design compelling, scalable, AI-native solutions.

This is a senior technical role at the intersection of enterprise architecture, pre-sales, solutioning, and delivery governance. You'll collaborate with leadership, engineering teams, and clients to architect solutions spanning AI integrations, RAG pipelines, agentic workflows, cloud infrastructure, and enterprise platforms.

This role requires a strong technical background and current hands-on expertise. Candidates with purely pre-sales experience or non-technical solutioning backgrounds will not be a fit.

Key Responsibilities

• Own end-to-end enterprise architecture for AI-native platforms, defining high-level and low-level designs across backend systems, data platforms, and AI components.
• Lead solutioning for complex enterprise engagements, translating client requirements into technically sound, secure, scalable, and commercially viable architectures.
• Define reference architectures and design standards for LLM integrations, RAG pipelines, agentic workflows, MCP-based integrations, and enterprise data platforms.
• Partner with pre-sales and business development teams to prepare RFP responses, technical proposals, solution presentations, and architecture documents.
• Lead client discovery sessions and technical presentations, communicating architectural decisions and trade-offs to technical and executive stakeholders.
• Conduct architecture reviews and technical assessments to ensure scalability

Senior AI Engineer

Company: Techjays

Experience: 4–8 Years

Location: Coimbatore, Hybrid

Joining: Immediate or within 30 days preferred

About the Role

We are looking for a Senior AI Engineer with strong Python development skills and hands-on experience building and deploying AI-powered applications. The ideal candidate should have practical knowledge of LLMs, Retrieval-Augmented Generation (RAG), vector databases, and scalable backend systems.

You will work closely with engineering and product teams to design, develop, and deploy reliable AI solutions for real-world business problems.

Key Responsibilities

• Design, develop, and maintain scalable backend applications using Python and frameworks such as Django, Flask, or FastAPI.
• Build and integrate AI-powered applications using LLMs, RAG pipelines, and agentic AI workflows.
• Develop document processing, embedding generation, semantic search, and retrieval pipelines.
• Integrate LLM APIs and optimize prompts, response quality, latency, and cost.
• Work with vector databases and relational databases to build efficient data retrieval systems.
• Design and implement REST APIs, asynchronous processing, caching, and queuing mechanisms.
• Apply software engineering best practices, including design patterns, clean code, testing, and version control.
• Deploy and maintain applications on AWS or GCP using Docker and CI/CD pipelines.
• Monitor production systems, troubleshoot issues, and improve application performance and reliability.
• Collaborate with cross-functional teams to translate business requirements into practical AI solutions.
• Contribute to code reviews, technical documentation, and knowledge sharing within the engineering team.

Required Skills

• 4–8 years of experience in software development, with strong hands-on Python expertise.
• Strong understanding of data structures, algorithms, object-oriented programming, and design patterns.
• Experience building backend applications using Django, Flask, or FastAPI.
• Hands-on experience with LLM-based applications and API integrations.
• Practical experience implementing RAG pipelines, embeddings, and semantic search.
• Experience with vector databases such as Pinecone, Qdrant, Weaviate, or Chroma.
• Strong knowledge of SQL and relational databases such as PostgreSQL or MySQL.
• Experience with caching, message queues, asynchronous processing, and WebSockets.
• Familiarity with AWS or GCP, Docker, Git, and CI/CD pipelines.
• Understanding of API design, system architecture, application security, and performance optimization.
• Experience testing, debugging, and maintaining production-grade applications.

Preferred Skills

• Experience building agentic AI applications and multi-agent workflows.
• Familiarity with LangChain, LangGraph, LlamaIndex, or similar frameworks.
• Knowledge of Model Context Protocol (MCP) and tool-calling mechanisms.
• Experience with LLM evaluation, hallucination reduction, and output quality monitoring.
• Familiarity with fine-tuning, model selection, and inference optimization.
• Experience with LLMOps, AI observability, and production monitoring.
• Knowledge of Kubernetes and microservices architecture.

What We’re Looking For

• Strong problem-solving and analytical skills.
• Ability to take ownership of features from development through deployment.
• Practical understanding of how to build reliable AI applications beyond prototypes.
• Ability to make sound technical decisions and explain architectural trade-offs.
• Good communication and collaboration skills.
• Willingness to learn, experiment, and work on challenging AI engineering problems.

Lead AI Engineer

Experience: 8+ Years

Location: Coimbatore / Hybrid

Joining: Immediate or within 30 days

About Techjays

At Techjays, we help businesses reimagine how they build, operate, and scale through AI. We focus on developing secure, scalable, production-grade AI solutions that solve real business problems and deliver measurable outcomes.

Our engineering team brings experience from organizations such as Google, NetApp, ADP, Cognizant Consulting, and Capgemini. We combine strong engineering fundamentals with an execution-focused mindset to build advanced AI systems for global clients.

About the Role

We are looking for a Lead AI Engineer to drive the architecture and development of scalable backend systems and AI-powered applications.

In this role, you will lead the technical design and implementation of Python-based systems, oversee LLM integrations and RAG pipelines, and develop agentic AI workflows for production environments. You will take ownership of complex engineering challenges, establish coding and architectural standards, and mentor engineers to deliver reliable, maintainable, and high-performing solutions.

This is a hands-on technical leadership role for someone who can translate complex requirements into practical engineering solutions and take them from design to production.

Key Responsibilities

1. Backend Engineering & System Architecture

• Design and develop scalable, secure backend systems using Python and frameworks such as Django or Flask.
• Architect RESTful APIs, WebSocket services, and distributed systems that support high-performance applications.
• Apply design patterns, algorithms, and data structures to solve complex engineering challenges.
• Design efficient database schemas, caching strategies, and data access patterns for scalable applications.
• Establish engineering standards for code quality, testing, maintainability, and system performance.

2. AI Engineering & LLM Integration

• Architect and implement LLM-powered applications, retrieval-augmented generation (RAG) pipelines, and agentic AI workflows.
• Develop solutions using vector databases, embeddings, semantic search, and prompt engineering.
• Build and optimize multi-agent systems, orchestration workflows, and tool integrations using frameworks such as LangChain and LlamaIndex.
• Implement Model Context Protocol (MCP) integrations where appropriate to connect AI systems with external tools and data sources.
• Evaluate model fine-tuning approaches and other techniques to improve AI performance where required.
• Establish LLMOps practices covering evaluation, observability, quality monitoring, and cost and latency optimization.

3. Cloud Infrastructure & Deployment

• Design and deploy cloud-native applications using AWS and GCP services.
• Build and maintain CI/CD pipelines using Jenkins, GitLab CI, GitHub Actions, or similar tools.
• Containerize applications using Docker and support deployment and operations in Linux environments.
• Implement reliable asynchronous processing and messaging using queuing systems.
• Improve system availability, scalability, security, and deployment reliability across production environments.

4. Technical Leadership & Engineering Excellence

• Own technical decisions across complex backend and AI engineering initiatives.
• Guide engineers in architecture, implementation, debugging, code reviews, and engineering best practices.
• Identify performance bottlenecks and drive improvements in application reliability and scalability.
• Collaborate with product managers, frontend engineers, data scientists, and other stakeholders to deliver effective solutions.
• Evaluate emerging AI technologies, frameworks, and tools, adopting them when they provide meaningful technical or business value.
• Take ownership of features from technical design through implementation, deployment, and production support.

Required Technical Skills

Backend Development

• Strong Python programming expertise.
• Experience with Django, Flask, RESTful APIs, and WebSockets.
• Strong understanding of object-oriented programming, design patterns, algorithms, and data structures.

Databases & Performance

• Experience with PostgreSQL, MySQL, MongoDB, or equivalent database technologies.
• Strong understanding of relational database design, query optimization, and performance tuning.
• Experience implementing caching strategies and asynchronous processing.

Cloud & DevOps

• Hands-on experience with AWS and/or GCP.
• Experience with Git, Docker, Linux, and CI/CD pipelines.
• Familiarity with queuing systems and distributed application architectures.

System Design

• Ability to design secure, scalable, and maintainable backend systems.
• Experience making architecture decisions involving performance, reliability, scalability, and operational complexity.

Preferred AI/ML Skills

• Large Language Models (LLMs) and prompt engineering.
• Retrieval-Augmented Generation (RAG) architecture.
• Vector databases such as Pinecone, ChromaDB, or equivalent.
• Embeddings, semantic search, and retrieval optimization.
• Agentic AI workflows and multi-agent orchestration.
• Model Context Protocol (MCP) and tool integrations.
• LangChain, LlamaIndex, or similar frameworks.
• Model fine-tuning and LLMOps practices.
• AI evaluation frameworks, observability, and production quality monitoring.
• Experience optimizing inference costs, response latency, and AI application performance.

What We're Looking For

• Strong engineering fundamentals: You can solve complex technical problems and design maintainable systems.
• Hands-on ownership: You take responsibility for solutions from concept through production.
• System-level thinking: You understand how architecture, performance, security, and scalability work together.
• Practical AI expertise: You can build and deploy AI-powered applications beyond prototypes and proof of concepts.
• Technical leadership: You guide engineers, improve code quality, and establish sound engineering practices.
• Structured problem-solving: You make thoughtful technical decisions in ambiguous and fast-moving environments.
• Clear communication: You collaborate effectively across engineering and business teams.
• Continuous improvement: You stay current with evolving AI technologies and apply them where they create value.
• 
  

What We Offer

• Competitive compensation.
• Flexible work environment with Coimbatore office and hybrid options.
• Paid holidays and flexible time off.
• Medical insurance for self and family, with coverage of up to ₹4 lakhs per person.
• Opportunities to architect and build production-grade AI systems used by real customers.
• Exposure to global clients and technically challenging projects.
• A culture that values ownership, clarity, integrity, and continuous learning.

AI Project Manager

About Techjays

At Techjays, we are driving the future of artificial intelligence with a bold mission to empower businesses worldwide by helping them build AI solutions that transform industries. As an established leader in the AI space, we combine deep expertise with a collaborative, agile approach to deliver impactful technology that drives meaningful change. Our global team consists of professionals from leading companies such as Google, Akamai, NetApp, ADP, and Cognizant.

Role Overview

We are seeking a seasoned Project Manager to oversee the successful delivery of complex AI-driven projects. You will be responsible for bridging organizational goals with cross-functional execution, ensuring that our technical teams deliver high-quality solutions on schedule and within budget.

Key Recruitment Details

• Experience Required: 8 + Years (Minimum 6+ years in end-to-end project management)
• Work Location: Coimbatore / Hybrid
• Target Joining Date: (ASAP / Within 30 days)

Must-Have Qualifications

• Proven Execution: 6+ years of experience managing the complete lifecycle of enterprise-grade software projects.
• Agile Expertise: Advanced proficiency in Agile/Scrum methodologies, with a track record of facilitating sprint planning, stand-ups, and retrospectives.
• Technical Proficiency: Mastery of project management tools including Jira, MS Project, or Trello.
• Strategic Planning: Demonstrated experience in resource allocation, risk mitigation, and contingency planning.
• AI Enthusiasm: Experience leveraging AI tools in project management or a demonstrated passion for adopting AI technologies to optimize workflows.
• Stakeholder Management: Exceptional communication skills for managing both internal cross-functional teams and external client relationships.

Roles & Responsibilities

• Project Governance: Plan, execute, and monitor projects to ensure alignment with client expectations and organizational benchmarks.
• Team Leadership: Facilitate high-performing Agile environments, fostering a culture of collaboration, innovation, and technical ownership.
• Risk & Budget Management: Identify potential bottlenecks early, implement mitigation strategies, and manage project budgets to ensure optimal resource utilization.
• Reporting & Transparency: Track project progress using modern metrics, preparing detailed reports and presentations for senior management.
• Continuous Improvement: Analyze project outcomes to implement best practices and drive operational discipline across the engineering organization.
• Mentorship: Elevate team members through active support and guidance, ensuring professional growth within the team.

Success Milestones

Timeline

Expectations

First 30 Days

Audit active project pipelines, establish stakeholder relationships, and assume management of ongoing sprint cycles.

First 60 Days

Optimize resource allocation workflows, streamline cross-team communication, and implement improved risk-tracking mechanisms.

First 90 Days

Achieve >85% sprint commitment completion rate and stabilize project delivery predictability across assigned teams.

What Techjays Offers

• Competitive Compensation: Best-in-class packages structured to reflect experience and impact.
• Health & Wellness: Medical insurance covering self and family up to ₹4 lakhs per person.
• Flexibility: A trust-based time-off policy and a flexible hybrid work model.
• Environment: A casual work culture with a diverse, multicultural team that respects ideas regardless of designation.
• Growth: Meaningful professional development in an innovation-driven culture.

Data Science (SME)

FACE Prep is India’s leading employability and industry-aligned education company. For over 17 years, we have partnered with higher education institutions to bridge the gap between academia and industry.

● Worked with 2,000+ colleges and universities across India

● Trained 6+ million students across disciplines

● Market leaders in:

● Employability skills & placement readiness

● Industry-aligned academic papers(credit-bearing)

● Full-scale industry-aligned degree programs with universities

● Pan-India operations, headquartered in Coimbatore

● Young, energetic, mission-driven team

● Fast-growing organization with headcount expected to cross 1,000 employees in the next financial year

At FACE Prep, people are the platform on which outcomes are built.

Position: Data Science (SME)

Location: Coimbatore

Duration: Full-Time

Department: Training & Development

Experience: Minimum 2 Years

Role Description :

The Data Science Subject Matter Expert (SME) is a full-time, on-site role based in Coimbatore. The SME will design and deliver data science curricula, including lectures, hands-on labs, and project-based learning for students preparing for tech careers. Daily responsibilities include creating educational content, developing problem sets and case studies, mentoring learners on data analysis and model-building, and reviewing student work to provide constructive feedback. The SME will collaborate with other trainers and the product team to align content with current industry practices and hiring requirements. The role also involves analyzing learner performance data, refining teaching strategies, and occasionally contributing to workshops, bootcamps, and online learning materials.

Requirements:

• Strong foundation in Statistics and Data Science, with the ability to explain complex concepts clearly and practically.

• Hands-on experience in Data Analytics and Data Analysis, including working with real-world datasets and deriving actionable insights.

• Excellent Analytical Skills for problem-solving, designing assignments, and guiding learners through data-driven decision-making.

• Proficiency in common data science tools and languages (e.g., Python/R, SQL, data visualization tools such as Tableau/Power BI).

• Prior experience in teaching, mentoring, corporate training, or curriculum development is highly beneficial.

• Bachelor’s or Master’s degree in a quantitative field such as Computer Science, Statistics, Mathematics, Data Science, or related discipline.

• Ability to communicate effectively with diverse learner groups and collaborate within a multidisciplinary team.

• Exposure to machine learning concepts, model evaluation, and deployment practices is a plus.

IMMEDIATE JOINERS REQUIRED

Your Responsibilities

what you will wake up to solve.

• Process-First AI Strategy: Principal Technical Expert: Act as a hands-on leader and the core technical authority tasked with "futurifying" client businesses through advanced AI. Take full ownership of the AI Engineering squad, transforming ambitious concepts into high-impact, tangible realities.
• Engineering & Intelligent Deployment: Execute the full-lifecycle development of innovative AI/ML solutions, including hands-on design, coding, testing, and deployment of robust, scalable systems that prioritize technical excellence and business relevance.
• Scalability & Architectural Optimization: Directly build and optimize high-performance AI architectures and core system components to ensure solutions are reliable, production-ready, and optimized for long-term operational success.
• Impact-Driven Technical Expertise: Deliver intelligent client outcomes through direct technical contribution, maintaining an "Always Beta" mindset and a relentless focus on solving complex engineering challenges.
• Leadership through Action: Lead by example rather than control, coaching and mentoring a high-performing squad of "happier Do-ers" to foster a vibrant culture of continuous innovation and technical excellence.
• Strategic Integration & Collaboration: Partner across internal teams to translate chaotic business challenges into precise technical requirements, ensuring seamless solution integration and adoption for global clients.
• The "Agentic" Shift: You will lead the transition from simple predictive models to Agentic Workflows. You will build systems where AI agents can plan, reason, and execute complex tasks autonomously to solve intricate business problems.
• Talent & Culture: You will mentor a high-performance squad of AI Engineers and Data Scientists. You will teach them to look beyond the algorithm and understand the business outcome.

Functional Skills

Scaling Intelligent Workforce through Delivery Excellence

• Deep Technical Acumen: Operates at the cutting edge of AI, applying advanced technical knowledge to engineer and implement groundbreaking solutions, and guide the squad in developing future capabilities.
• Client Advocacy & Revenue Growth: Skill in cultivating and maintaining trusted client partnerships. Drives strategic engagement that results in repeat business and expanded client portfolios within the region.
• Contract & Risk Governance: High proficiency in reviewing and managing complex project agreements (SoW), mitigating delivery risks, and navigating commercial negotiations to safeguard BU profitability.
• Structured Problem-Solving: Simplifies chaotic technical challenges for the squad by breaking them into solvable chunks using first-principles thinking.
• Squad Delivery Ownership: Follows through on the squad's solution execution—owning technical outcomes from ideation to deployment with rigor, precision, and pride, ensuring tangible, real-world business value.

Technical Oversight & Execution Charter

• Technical Troubleshooting & Crisis Resolution: Actively manages technical roadblocks within the squad, personally intervening to troubleshoot ML or MLOps constraints. You ensure the protection of sprint timelines and the guaranteed performance of deployed models through hands-on problem-solving.
• Cloud-Native Technical Command: Maintains deep, functional knowledge of modern AI system design (e.g., RAG Frameworks, Agentic Workflows, and Inference Optimization) across GCP and AWS. You hold the responsibility to validate squad-level technical roadmaps, ensuring they are technically feasible and production-hardened.
• End-to-End Project Management: Expertly manage all aspects of a project, including scope, budget, timelines, and stakeholder communication. Accountable for the entire delivery, not just the technical parts.
• Talent Strategy & Mentorship: Drive the hiring and development of specialized talent. You will be responsible for defining and optimizing effective team structures while proactively fostering an environment that champions creative problem-solving and technical agility.

Tech Superpowers

• Deep AI Engineering Mastery & Guidance: Possesses profound, hands-on expertise in engineering, optimizing, and deploying foundational models, custom AI solutions, and complex multi-modal systems. You'll also guide your squad in understanding model architectures, training methodologies, and ethical AI development from the ground up, ensuring their collective proficiency.
• Intelligent Systems Architecture & Oversight: You'll directly contribute to and oversee the coding and implementation of robust, scalable, and production-grade AI platforms and MLOps components for your squad's projects. You'll translate abstract technical requirements into high-performance, maintainable AI system designs, always considering reliability, security, and future extensibility across the squad's work.
• Cloud-Native AI capability: More than cloud-certified, you are deeply cloud-capable in applied AI engineering. You proficiently leverage and guide your team in utilizing leading cloud AI/ML ecosystems to build, deploy, and manage AI solutions.
• Technical Integrity & Ethical Governance: Establishes and audits mandatory technical quality benchmarks, ensuring strict adherence to rigorous policies regarding model validation, automated testing coverage, and ethical governance.

Experience & Relevance

• A value-driven AI/ML Engineering Manager with 8+ years of experience in building and scaling end-to-end AI engineering and solution delivery.
• Leadership Track Record: Proven track record as a hands-on builder, and lead, contributing to the design, development, and deployment of complex, enterprise-grade AI/ML platforms and solutions. Expert in leveraging Google Cloud's AI/ML ecosystem (Vertex AI, BigQuery ML, GKE for MLOps) to deliver highly performant, scalable, and impactful AI transformations.
• Delivery & Advisory Record: Experience in building and optimizing intelligent systems and personally driving the technical execution from conception to scalable deployment.
• Applied AI & Domain Expertise: Hands-On AI Deployment: Extensive hands-on experience deploying AI-powered workflows, copilots, and automation solutions in production environments.
• Client-Facing Lead: Demonstrated hands-on experience as an AI/ML Product Manager, Data Science Manager, or Technical Architect in client-facing capacities. This involves directly building, implementing, and advising on complex AI solutions, consistently acting as the trusted technical authority for strategic clients.

Bonus Points (you will thrive if you have)

• Founder’s Energy: Bias for action, thrive in ambiguity, relentless focus on outcomes.
• Low-Code/No-Code Fluency: Experience with AI integrations via Power Platform or similar.
• AI Copilots & Extensions: Built plugins, copilots, or agentic automation frameworks.
• Thought Leadership DNA: Industry content creation, technical blogs, public speaking.
• Ethical Compass: Strong commitment to responsible AI practices.
• Engineer at Heart: Background in product development or engineering before moving into architecture.

Your Responsibilities

what you will wake up to solve.

• Process-First AI Strategy: Principal Technical Expert: Act as a hands-on leader and the core technical authority tasked with "futurifying" client businesses through advanced AI. Take full ownership of the AI Engineering squad, transforming ambitious concepts into high-impact, tangible realities.
• Engineering & Intelligent Deployment: Execute the full-lifecycle development of innovative AI/ML solutions, including hands-on design, coding, testing, and deployment of robust, scalable systems that prioritize technical excellence and business relevance.
• Scalability & Architectural Optimization: Directly build and optimize high-performance AI architectures and core system components to ensure solutions are reliable, production-ready, and optimized for long-term operational success.
• Impact-Driven Technical Expertise: Deliver intelligent client outcomes through direct technical contribution, maintaining an "Always Beta" mindset and a relentless focus on solving complex engineering challenges.
• Leadership through Action: Lead by example rather than control, coaching and mentoring a high-performing squad of "happier Do-ers" to foster a vibrant culture of continuous innovation and technical excellence.
• Strategic Integration & Collaboration: Partner across internal teams to translate chaotic business challenges into precise technical requirements, ensuring seamless solution integration and adoption for global clients.
• The "Agentic" Shift: You will lead the transition from simple predictive models to Agentic Workflows. You will build systems where AI agents can plan, reason, and execute complex tasks autonomously to solve intricate business problems.
• Talent & Culture: You will mentor a high-performance squad of AI Engineers and Data Scientists. You will teach them to look beyond the algorithm and understand the business outcome.

Functional Skills

1. Scaling Intelligent Workforce through Delivery Excellence

• Deep Technical Acumen: Operates at the cutting edge of AI, applying advanced technical knowledge to engineer and implement groundbreaking solutions, and guide the squad in developing future capabilities.
• Client Advocacy & Revenue Growth: Skill in cultivating and maintaining trusted client partnerships. Drives strategic engagement that results in repeat business and expanded client portfolios within the region.
• Contract & Risk Governance: High proficiency in reviewing and managing complex project agreements (SoW), mitigating delivery risks, and navigating commercial negotiations to safeguard BU profitability.
• Structured Problem-Solving: Simplifies chaotic technical challenges for the squad by breaking them into solvable chunks using first-principles thinking.
• Squad Delivery Ownership: Follows through on the squad's solution execution—owning technical outcomes from ideation to deployment with rigor, precision, and pride, ensuring tangible, real-world business value.

2. Technical Oversight & Execution Charter

• Technical Troubleshooting & Crisis Resolution: Actively manages technical roadblocks within the squad, personally intervening to troubleshoot ML or MLOps constraints. You ensure the protection of sprint timelines and the guaranteed performance of deployed models through hands-on problem-solving.
• Cloud-Native Technical Command: Maintains deep, functional knowledge of modern AI system design (e.g., RAG Frameworks, Agentic Workflows, and Inference Optimization) across GCP and AWS. You hold the responsibility to validate squad-level technical roadmaps, ensuring they are technically feasible and production-hardened.
• End-to-End Project Management: Expertly manage all aspects of a project, including scope, budget, timelines, and stakeholder communication. Accountable for the entire delivery, not just the technical parts.
• Talent Strategy & Mentorship: Drive the hiring and development of specialized talent. You will be responsible for defining and optimizing effective team structures while proactively fostering an environment that champions creative problem-solving and technical agility.

Tech Superpowers

• Deep AI Engineering Mastery & Guidance: Possesses profound, hands-on expertise in engineering, optimizing, and deploying foundational models, custom AI solutions, and complex multi-modal systems. You'll also guide your squad in understanding model architectures, training methodologies, and ethical AI development from the ground up, ensuring their collective proficiency.
• Intelligent Systems Architecture & Oversight: You'll directly contribute to and oversee the coding and implementation of robust, scalable, and production-grade AI platforms and MLOps components for your squad's projects. You'll translate abstract technical requirements into high-performance, maintainable AI system designs, always considering reliability, security, and future extensibility across the squad's work.
• Cloud-Native AI capability: More than cloud-certified, you are deeply cloud-capable in applied AI engineering. You proficiently leverage and guide your team in utilizing leading cloud AI/ML ecosystems to build, deploy, and manage AI solutions.
• Technical Integrity & Ethical Governance: Establishes and audits mandatory technical quality benchmarks, ensuring strict adherence to rigorous policies regarding model validation, automated testing coverage, and ethical governance.

Experience & Relevance

• A value-driven AI/ML Engineering Manager with 8+ years of experience in building and scaling end-to-end AI engineering and solution delivery.
• Leadership Track Record: Proven track record as a hands-on builder, and lead, contributing to the design, development, and deployment of complex, enterprise-grade AI/ML platforms and solutions. Expert in leveraging Google Cloud's AI/ML ecosystem (Vertex AI, BigQuery ML, GKE for MLOps) to deliver highly performant, scalable, and impactful AI transformations.
• Delivery & Advisory Record: Experience in building and optimizing intelligent systems and personally driving the technical execution from conception to scalable deployment.
• Applied AI & Domain Expertise: Hands-On AI Deployment: Extensive hands-on experience deploying AI-powered workflows, copilots, and automation solutions in production environments.
• Client-Facing Lead: Demonstrated hands-on experience as an AI/ML Product Manager, Data Science Manager, or Technical Architect in client-facing capacities. This involves directly building, implementing, and advising on complex AI solutions, consistently acting as the trusted technical authority for strategic clients.

Bonus Points (you will thrive if you have)

• Founder’s Energy: Bias for action, thrive in ambiguity, relentless focus on outcomes.
• Low-Code/No-Code Fluency: Experience with AI integrations via Power Platform or similar.
• AI Copilots & Extensions: Built plugins, copilots, or agentic automation frameworks.
• Thought Leadership DNA: Industry content creation, technical blogs, public speaking.
• Ethical Compass: Strong commitment to responsible AI practices.
• Engineer at Heart: Background in product development or engineering before moving into architecture.

Why you’ll love being a ‘Searcian’

NOT your ‘usual’ management consultancy; we ‘solve differently’.

• We are happier. No really happier’: A vibrant, inclusive, and supportive work environment. We even have a dedicated role for ‘Better Living’.
• The Company You Keep (Says Everything): solvers. engineers. tinkerers. improvers. futurists operating across 12 countries.
• No room for CAVEers (Constantly Against Virtually Everything people). Instead, we make room for a meditation room in our offices.
• No bloat: 27 people meeting with 23 clueless people. Not happening here. We also don't do the meetings to plan for pre-meetings.
• No bureaucracy. Zero entropy. Real decision-making velocity: We’re large enough to solve the world’s most complex business challenges, yet small and agile enough to value individual humans. With us, you’re a name, not an employee ID number lost in a sea of 37,000 people where it takes a year just to decide ‘who will decide’.
• Ideas over Hierarchy: We reject HiPPOs (Highest Paid Person’s Opinion). The most well-reasoned ideas win - regardless of whose name is on them. That dangerous phrase, "We’ve always done it this way," dies here.
• Own-the-outcome: The buck stops with you. Doesn’t matter if you are an intern. (Psst: A ‘real intern’ actually drafted this JD.)
• Expert ‘wholesome generalists’, Not ‘one-nut-tighteners’. At Searce, you see the whole picture — how the car is designed, built, and driven — not just how to tighten the third nut on a red 1962 Ford Falcon owned by Vinny’s cousin. Real impact comes from knowing why that nut matters to the person behind the wheel.
• You ‘do stuff’ that matters. Not just “follow up on the deck we shared.”
• Gain more years in your Searce-perience: We operate at a 3.65x experience velocity—yes, we measured it. (and charted it to the scale too)

Join the ‘real solvers’

ready to futurify?

If you are excited by the possibilities of what an AI-native engineering-led, modern tech consultancy can do to futurify businesses, apply here and experience the ‘Art of the possible’. Don’t Just Send a Resume. Send a Statement.

AI Lead (Backend Systems & Architecture)

This is not a feature-delivery role. This is an architecture, ownership, and AI systems leadership role.

At Techjays, we build production-grade AI platforms for global clients. We are looking for an AI Lead with strong backend engineering expertise—someone who can design, scale, and take complete ownership of intelligent systems end-to-end.

You will operate at the intersection of backend engineering, distributed systems, and applied AI, driving both technical direction and execution.

What You’ll Do

• Architect and scale backend systems powering AI-driven applications
• Design and implement AI workflows such as RAG pipelines, agents, and LLM integrations
• Own systems end-to-end: architecture, development, deployment, and scaling
• Build reliable, high-performance distributed systems
• Integrate and optimize LLMs (Claude, GPT, etc.) for real-world use cases
• Lead backend and AI initiatives with strong technical ownership
• Ensure performance, scalability, observability, and cost efficiency
• Mentor engineers and raise the technical bar across teams
• Collaborate with product and AI teams to build AI-native solutions

What We’re Looking For

• Proven experience in architecting and scaling backend systems end-to-end
• Strong expertise in Python (Django / Flask / FastAPI)
• Deep understanding of distributed systems and system design
• Hands-on experience with AWS or GCP in production environments
• Solid experience working with LLMs (Claude, GPT, etc.)
• Strong knowledge of:
• Retrieval-Augmented Generation (RAG)
• Vector databases (Pinecone, FAISS, Weaviate, etc.)
• Experience in building and managing microservices architectures
• Ability to lead teams, mentor engineers, and drive technical excellence
• Strong problem-solving skills with an ownership mindset

Nice to Have

• Experience building AI agents or autonomous systems
• Familiarity with real-time data systems or streaming (Kafka, etc.)
• Understanding of MLOps and AI system lifecycle
• Experience optimizing AI systems for latency, cost, and scalability

Who You Are

• You think in systems, not just features
• You take full ownership of what you build
• You are comfortable in fast-moving, ambiguous environments
• You stay updated with the latest advancements in AI and backend technologies

This role is ideal for someone who wants to lead, build, and scale AI-powered backend systems in production while driving real-world impact.

Position: Assistant Professor

Department: CSE / IT

Experience: 0 – 15 Years

Joining: Immediate / Within 1 Month

Salary: As per norms and experience

🎓 Qualification:

ME / M.Tech in Computer Science Engineering / Information Technology

Ph.D. (Preferred but not mandatory)

First Class in UG & PG as per AICTE norms

🔍 Roles & Responsibilities:

Deliver high-quality lectures for UG / PG programs

Prepare lesson plans, course materials, and academic content

Guide student projects and internships

Participate in curriculum development and academic planning

Conduct internal assessments, evaluations, and result analysis

Mentor students for academic and career growth

Participate in departmental research activities

Publish research papers in reputed journals (Scopus/SCI preferred)

Attend Faculty Development Programs (FDPs), workshops, and conferences

Contribute to NAAC / NBA accreditation processes

Support institutional administrative responsibilities

💡 Required Skills:

Strong subject knowledge in CSE / IT domains

Programming proficiency (Python, Java, C++, Data Structures, AI/ML, Cloud, etc.)

Excellent communication and presentation skills

Research orientation and academic enthusiasm

Team collaboration and mentoring ability

Role: Senior AI Engineer

Work Location: TechGenzi Coimbatore Office (ODC for Tiramai.ai)

Employment Type: Full-time

Experience: 2–5 years (Full-stack development with AI exposure)

About the Role & Work Location.

The selected candidate will be employed by Tiramai.ai and will work exclusively on Tiramai.ai projects. The role will be based out of TechGenzi’s Coimbatore office, which functions as an Offshore Development Center (ODC) supporting Tiramai.ai’s product and engineering initiatives.

Primary Focus

As an AI Engineer at our enterprise SaaS and AI-native organization, you will play a pivotal role in building secure, scalable, and intelligent digital solutions. This role combines full-stack development expertise with applied AI skills to create next-generation platforms that empower enterprises to modernize and act smarter with AI. You will work on AI-driven features, APIs, and cloud-native applications that are production-ready, compliance-conscious, and aligned with our mission of delivering responsible AI innovation.

Key Responsibilities

• Design, develop, and maintain full-stack applications using Python (backend) and React/Angular (frontend).
• Build and integrate AI-driven modules, leveraging GenAI, ML models, and AI-native tools into enterprise-grade SaaS products.
• Develop scalable REST APIs and microservices with security, compliance, and performance in mind.
• Collaborate with architects, product managers, and cross-functional teams to translate requirements into production-ready features.
• Ensure adherence to secure coding standards, data privacy regulations, and human-in-the-loop AI principles.
• Participate in code reviews, system design discussions, and continuous integration/continuous deployment (CI/CD) practices.
• Contribute to reusable libraries, frameworks, and best practices to accelerate AI platform development.

Skills Required

• Strong proficiency in Python for backend development.
• Frontend expertise in React.js or Angular with 2+ years of experience.
• Hands-on experience in full SDLC development (design, build, test, deploy, maintain).
• Familiarity with AI/ML frameworks (e.g., TensorFlow, PyTorch) or GenAI tools (LangChain, vector DBs, OpenAI APIs).
• Knowledge of cloud-native development (AWS/Azure/GCP), Docker, Kubernetes, and CI/CD pipelines.
• Strong understanding of REST APIs, microservices, and enterprise-grade security standards.
• Ability to work collaboratively in fast-paced, cross-functional teams with strong problem-solving and analytical skills.
• Exposure to responsible AI principles (explainability, bias mitigation, compliance) is a plus.

Growth Path

• AI Engineer (24 years) focus on full-stack + AI integration, delivering production-ready features.
• Senior AI Engineer (4–6 years) lead modules, mentor juniors, and drive AI feature development at scale.
• Lead AI Engineer (6–8 years) own solution architecture for AI features, ensure security/compliance, collaborate closely with product/tech leaders.
• AI Architect / Engineering Manager (8+ years) shape AI platform strategy, guide large-scale deployments, and influence product/technology roadmap.

Are you a motivated individual eager to launch your career in generative AI and learn advanced technologies? Are you a hands-on learner with an interest in large language models and emerging AI technologies? Do you possess the ability to collaborate effectively within a team environment to implement and learn technical solutions?

At Aivar, we're looking for entry-level architects and engineers to learn generative AI techniques and contribute to building innovative solutions under the guidance of experienced professionals.

As an Generative AI/ML Engineer, you'll learn from technology and business teams while developing solutions. You will gain hands-on experience in a fast-paced environment that contributes to innovative AI projects.

Key job responsibilities:

● Learn to implement large language model solutions using Amazon Web Services (AWS)

● Learn Generative AI frameworks (LangChain, LangSmith, HuggingFace)

● Support prompt engineering implementation

● Assist in fine-tuning pipelines for specific use cases

● Learn to build basic generative AI solutions for text and images

● Help implement RAG architectures

● Support MLOps/LLMOps practices

● Document implementations and learnings

● Assist in testing generative AI solutions

Job Title: Data Science Trainer

Location: Coimbatore

Employment Type: Full-time

Job Summary:

We are seeking an experienced and passionate Data Science Trainer to deliver engaging and practical training sessions to students or professionals. The trainer will design curriculum, prepare materials, and guide learners in developing data science skills through real-world projects and case studies.

Key Responsibilities:

• Develop and deliver comprehensive training programs on Data Science concepts, tools, and techniques.
• Teach topics including but not limited to:
• Data Analysis (NumPy, Pandas, Data Cleaning, EDA)
• Data Visualization (Matplotlib, Seaborn, Plotly)
• Statistics & Probability (Descriptive, Inferential)
• Machine Learning (Supervised & Unsupervised Algorithms, Model Evaluation)
• Deep Learning (Neural Networks, TensorFlow, PyTorch – if applicable)
• Big Data Tools (Hadoop, Spark – if applicable)
• Provide hands-on training with industry-relevant datasets and projects.
• Prepare lesson plans, assignments, assessments, and evaluation reports.
• Mentor learners individually to ensure conceptual clarity and practical application.
• Keep training content updated with the latest industry trends and technologies.
• Collaborate with the academic or corporate training team for curriculum improvement.

Required Skills & Qualifications:

• Bachelor’s/Master’s degree in Computer Science, Statistics, Mathematics, or related field.
• Proven experience in Data Science, Machine Learning, and Data Analytics.
• Proficiency in Python (NumPy, Pandas, Scikit-learn, etc.) and SQL.
• Strong understanding of statistical concepts and their application in data analysis.
• Experience with visualization tools like Tableau/Power BI is a plus.
• Excellent communication and presentation skills.
• Ability to simplify complex concepts for learners with varied backgrounds.
• Prior teaching/training experience preferred.

Role Description

This is a full-time on-site role for the Head of Artificial Intelligence at KGiSL Educational Institutions, located in Coimbatore. The Head of Artificial Intelligence will be responsible for overseeing and developing AI strategies and initiatives. Daily tasks include leading AI research projects, developing innovative AI solutions, managing a team of AI professionals, and collaborating with various departments to integrate AI methodologies into different functions. The role also involves staying current with industry advancements and ensuring compliance with ethical and regulatory standards.

Qualifications

• Strong background in Computer Science and Data Science
• Extensive experience in Pattern Recognition, Natural Language Processing (NLP), and Computer Vision
• Proven leadership and team management skills
• Excellent problem-solving and analytical skills
• Advanced degree Master's in a related field
• Strong communication and collaboration skills
• Experience in the educational sector is a plus
• 8 Years of experience in Artificial Intelligence

We are looking for a skilled and detail-oriented Data Analyst – Data Scientist (DA-DS) to join our team. This hybrid role involves analyzing large datasets to extract insights, build predictive models, and support data-driven decision-making. You’ll work closely with cross-functional teams to transform raw data into actionable insights using statistical techniques, data visualization, and machine learning tools.

Role: Graphic Designer

Experience: 0-3 years

Location: Ambattur, Chennai

Responsibilities:

● Collaborate with the marketing and creative teams to understand design requirements, objectives, and target audience.

● Develop design concepts, graphics, and layouts based on the project briefs and brand guidelines.

● Create visually appealing designs for various marketing materials, including digital and print assets such as brochures, flyers, banners, social media graphics, and website elements.

● Produce high-quality illustrations, icons, and infographics that effectively communicate complex ideas and information.

● Select colors, typography, and imagery that align with the brand identity and project goals.

● Ensure all designs are visually cohesive and consistent across different platforms and channels.

● Utilize industry-standard design software and tools to create and edit graphics, such as Adobe Creative Suite (Photoshop, Illustrator, InDesign).

● Collaborate with the creative team to brainstorm and contribute innovative design ideas and concepts.

● Manage multiple design projects simultaneously while adhering to project timelines and deadlines.

● Stay updated with design trends, techniques, and best practices, and incorporate them into design projects.

● Maintain and organize design files, assets, and documentation for easy accessibility and future reference.

● Work closely with external vendors, printers, and other partners to ensure accurate and high-quality production of design materials.

● Incorporate feedback and iterate designs based on stakeholder input and requirements.

● Contribute to the continuous improvement of design processes and workflows.

Requirements:

● Bachelor's degree in graphic design, visual communication, or a related field.

● Minimum 0-3 years work experience as a Graphic Designer or in a similar role.

● Proficiency in using industry-standard design software, such as Adobe Creative Suite (Photoshop, Illustrator, InDesign).

● Strong portfolio showcasing a diverse range of design projects and styles.

● Excellent understanding of design principles, typography, color theory, and layout composition.

● Creative thinking and the ability to generate innovative design concepts and solutions.

● Strong attention to detail and a keen eye for aesthetics.

● Good communication and collaboration skills to work effectively with cross-functional teams.

● Ability to manage multiple projects simultaneously and meet deadlines.

● Knowledge of digital design principles and formats for online platforms.

● Familiarity with print production processes and specifications.

● Familiarity with UX/UI design principles and an understanding of user-centered design is a plus.

● Knowledge of motion graphics and video editing software is a plus.

Note: Send your Resume attached with Portfolio

Let’s get started on building your path to success!

To prepare placement students with the technical knowledge, skills, and confidence required to succeed in campus recruitment drives, technical interviews, and entry-level job roles in the industry.

We are looking for a highly capable machine learning engineer to optimize our machine learning systems. You will be evaluating existing machine learning (ML) processes, performing statistical analysis to resolve data set problems, and enhancing the accuracy of our AI software's predictive automation capabilities.

To ensure success as a machine learning engineer, you should demonstrate solid data science knowledge and experience in a related ML role. A first-class machine learning engineer will be someone whose expertise translates into the enhanced performance of predictive automation software.

Machine Learning Engineer Responsibilities:

Consulting with managers to determine and refine machine learning objectives.

Designing machine learning systems and self-running artificial intelligence (AI) software to automate predictive models.

Transforming data science prototypes and applying appropriate ML algorithms and tools.

Ensuring that algorithms generate accurate user recommendations.

Turning unstructured data into useful information by auto-tagging images and text-to-speech conversions.

Solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks.

Developing ML algorithms to analyze huge volumes of historical data to make predictions.

Running tests, performing statistical analysis, and interpreting test results.

Documenting machine learning processes.

Keeping abreast of developments in machine learning.

Machine Learning Engineer Requirements:

Bachelor's degree in computer science, data science, mathematics, or a related field.

Master’s degree in computational linguistics, data analytics, or similar will be advantageous.

At least two years' experience as a machine learning engineer.

Advanced proficiency with Python, Java, and R code writing.

Extensive knowledge of ML frameworks, libraries, data structures, data modeling, and software architecture.

In-depth knowledge of mathematics, statistics, and algorithms.

Superb analytical and problem-solving abilities.

Great communication and collaboration skills.

Excellent time management and organizational abilities.

FURIOUS FOX is looking for Embedded Developers with strong coding skills in C & C++ as well as experience with Embedded Linux.

Experience : (Minimum 7-10 yrs)

• Experienced in edge processing for connected building / industrial / consumer

appliances / automotive ECU

• Have a good understanding of IoT platforms and architecture

• Deep experience in operating systems eg: Linux, freeRTOS / kernel development/device drivers.

/ sensor drivers

• Have experience with various low-level communication protocols, memory devices, messaging

framework etc.

• Have a deep understanding of design principles, design patterns, container preparations

• Have developed hardware, OS abstraction layers, and sensor handlers services to manage various BSP, os standards

• Have experience with Python edge packages.

• Have a good understanding about IoT databases for edge computing

• Good understanding of connectivity application protocols and connectivity SDK for Wi-Fi and BT / BLE

• Experienced in arm architecture, peripheral devices and hardware board configurations

• Able to set up debuggers, configure build environments, and compilers and optimize code and performance.

Skills / Tools:

• Expert at object-oriented programming

• Modular programming

• C / C++ / JavaScript / Python

• Eclipse framework

• Target deployment techniques

• IoT framework

• Test framework

Highlights :

• Having AI / ML knowledge in applications

• Have worked on wireless protocols

• Ethernet / Wi-Fi / Bluetooth / BLE

• Highly exploratory attitude

• willing to venture in and learn new

technologies.

• Have done passionate projects based on self-interest.