Techjays

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.

TECHJAYS

Senior Account Manager

Position: Senior Account Manager

Experience: 10+ Years

Industry: IT Services / Software Development / Technology Consulting

Location: Coimbatore / Hybrid

Joining: Immediate / Within 30 Days

Primary Skills: Enterprise Account Management, Strategic Client Relationships, Revenue Growth, Account Expansion, Consultative Selling, Commercial Negotiations, Account Profitability, Stakeholder Management.

Preferred Skills: AI/ML Services, Digital Transformation, Enterprise Software, HubSpot CRM, International Account Management, Agile Delivery.

About Techjays

At Techjays, we're helping businesses reimagine how they build, operate, and scale with AI at the core. We partner with organizations worldwide to design and deliver AI-powered software solutions that solve complex business challenges and create measurable business value.

Our global team brings together experienced technology professionals from organizations such as Google, Akamai, NetApp, ADP, Cognizant Consulting, and Capgemini.

We work with clients ranging from innovative startups to large enterprises, delivering custom AI solutions, software engineering services, and digital transformation initiatives.

We're looking for a Senior Account Manager who can take ownership of strategic client relationships, drive account growth, and build long-term partnerships with enterprise customers.

This role goes beyond traditional account management. You will be responsible for understanding client business objectives, identifying new opportunities, growing existing engagements, managing commercial relationships, and ensuring long-term account success.

The ideal candidate combines strong business acumen, consultative selling capabilities, commercial ownership, and the ability to engage confidently with senior executive stakeholders.

Key Responsibilities

1. Strategic Account & Client Relationship Management

• Own and manage a portfolio of strategic enterprise accounts, acting as the primary point of contact for client leadership.
• Build and maintain strong relationships with CXOs, VPs, Directors, and other key decision-makers.
• Understand client business objectives, technology roadmaps, operational challenges, and long-term priorities.
• Develop strategic account plans covering revenue targets, stakeholder mapping, growth opportunities, risks, and client retention.
• Act as a trusted advisor to clients, identifying opportunities where technology and AI solutions can create business value.
• Maintain strong client engagement throughout discovery, solutioning, project execution, and account expansion.

2. Revenue Growth & Business Development

• Own annual account revenue targets and drive consistent growth across assigned accounts.
• Identify opportunities for upselling, cross-selling, new projects, additional engineering teams, and new service offerings.
• Develop account expansion strategies based on client requirements and emerging business opportunities.
• Lead consultative discovery discussions to understand business challenges and identify potential technology solutions.
• Build business cases, ROI models, and commercial proposals to support client investment decisions.
• Maintain a healthy sales pipeline and provide accurate revenue forecasts.
• Drive renewals, contract extensions, and long-term engagement opportunities.

3. Commercial Ownership & Negotiations

• Lead commercial discussions and negotiations involving pricing, contracts, and engagement models.
• Manage Master Service Agreements (MSAs), Statements of Work (SOWs), rate cards, renewals, and change requests.
• Monitor account revenue, gross margins, delivery costs, and overall profitability.
• Identify commercial risks and take proactive measures to protect account margins.
• Work closely with finance, pre-sales, and delivery teams to ensure commercial commitments are realistic and sustainable.
• Balance client expectations with business objectives and organizational profitability.

4. Delivery Governance & Client Success

• Partner with engineering and delivery leaders to ensure projects meet agreed scope, quality, timelines, and commercial expectations.
• Participate in project planning, scoping discussions, and SOW preparation.
• Establish account governance through regular client reviews, monthly business reviews, steering committee meetings, and Quarterly Business Reviews (QBRs).
• Monitor client satisfaction, account health, delivery performance, and potential relationship risks.
• Manage senior-level escalations and lead recovery plans for at-risk accounts.
• Ensure effective communication between clients and internal delivery teams.
• Stay involved beyond contract closure to ensure successful execution and long-term client retention.

5. Consultative Selling & Solutioning

• Work closely with pre-sales and technical teams to understand client requirements and develop relevant technology solutions.
• Lead client discovery sessions and translate business challenges into solution opportunities.
• Drive proposals, solution presentations, and commercial discussions.
• Position Techjays' AI, software engineering, automation, and digital transformation capabilities based on client business needs.
• Communicate the business value, expected outcomes, and ROI of proposed solutions.
• Ensure that client expectations and commercial commitments are aligned with actual delivery capabilities.

6. Leadership & Account Management Excellence

• Mentor and guide junior account managers and support the development of account management capabilities.
• Establish structured account management processes, playbooks, reporting standards, and account health metrics.
• Improve pipeline visibility, revenue forecasting, and account performance reporting through CRM systems.
• Share market intelligence, client feedback, and growth opportunities with senior leadership.
• Contribute to service offering development and go-to-market strategies based on client insights.

Required Skills & Experience

Account Management & Enterprise Sales

• 10+ years of experience in enterprise account management, strategic client management, or consultative sales within the IT services or software industry.
• Proven track record of managing and growing high-value enterprise accounts.
• Demonstrated experience in account expansion, upselling, cross-selling, renewals, and revenue generation.
• Strong experience managing long-term, complex client engagements and multiple stakeholders.
• Experience handling international clients and global enterprise accounts.

Business & Commercial Acumen

• Strong understanding of account revenue, gross margins, profitability, pricing, and commercial planning.
• Hands-on experience negotiating MSAs, SOWs, rate cards, contract renewals, and change requests.
• Ability to develop account growth strategies, business cases, and ROI models.
• Experience managing revenue forecasts, sales pipelines, and account financial performance.
• Understanding of IT services engagement models, including Fixed Price, Time & Material (T&M), and Dedicated Teams.

Client & Stakeholder Management

• Proven ability to engage with CEOs, CFOs, COOs, VPs, and senior technology leaders.
• Strong consultative discovery and executive-level communication skills.
• Ability to identify key decision-makers, understand stakeholder dynamics, and influence complex buying decisions.
• Experience managing client escalations, resolving relationship challenges, and turning around at-risk accounts.

Technology & Delivery Understanding

• Good understanding of the software development lifecycle (SDLC), software engineering, and technology delivery models.
• Familiarity with AI/ML, automation, enterprise software, and digital transformation services.
• Ability to collaborate effectively with engineering, pre-sales, product, and delivery teams.
• Understanding of Agile methodologies and distributed delivery environments.

Tools & Reporting

• Hands-on experience with CRM platforms, preferably HubSpot.
• Familiarity with pipeline management, revenue forecasting, account reporting, and account health metrics.
• Strong presentation, negotiation, and business communication skills.

What We're Looking For Beyond Skills

• Business Ownership: Takes responsibility for account revenue, profitability, retention, and long-term growth.
• Strategic Thinking: Understands the bigger business picture and identifies opportunities beyond immediate client requirements.
• Executive Presence: Can confidently engage with senior decision-makers and build trusted business relationships.
• Commercial Mindset: Understands the balance between client satisfaction, delivery commitments, revenue, and profitability.
• Consultative Approach: Asks the right questions, understands business challenges, and positions solutions that deliver measurable value.
• Accountability: Remains involved throughout the client lifecycle, from opportunity discovery to successful delivery and expansion.
• Problem-Solving: Handles difficult client situations, escalations, and commercial challenges with a structured approach.
• Leadership: Can guide internal teams, mentor junior account managers, and influence stakeholders without relying on formal authority.

Nice to Have

• Experience building or scaling an account management function.
• Experience developing account management processes, playbooks, and performance metrics from scratch.
• Previous experience mentoring or leading a team of account managers.
• Familiarity with AI/ML services, intelligent automation, and enterprise AI solutions.
• Experience working with global clients and distributed engineering teams.
• MBA or relevant postgraduate qualification.

Join Techjays

If you're someone who can build lasting enterprise relationships, identify business opportunities, drive account revenue, and turn client partnerships into long-term business growth, we'd love to hear from you.

About the Role

• We're hiring a Partnerships Manager to drive revenue through our cloud and AI partner ecosystem. This is a
• sales-oriented alliances role — we need someone who has already built relationships with Field Sales Reps
• (FSRs) and Account Executives at Google Cloud, AWS, or Azure, and has a track record of converting
• those relationships into closed deals. You'll shape how we approach partnership-led sales strategically, not
• just manage program operations.

What You'll Do

• Build and leverage relationships with FSRs and Account Executives at Google Cloud, AWS, and

Azure to generate qualified pipeline

• Drive co-sell motions end-to-end — from partner-sourced lead to closed deal

• Define and execute our partnership-led sales strategy, advising leadership on where and how to

prioritize partner channels

• Identify and pursue joint-selling opportunities with hyperscaler account teams

• Represent the company in partner-facing sales conversations and deal reviews

• Track partner-sourced pipeline and revenue, and report on channel performance to leadership

• Work around partner-led sales incentives, collaborating with external partnership teams for funding

initiatives

• Expand our footprint within the Google Cloud, AWS, and Azure partner ecosystems by building new

FSR/AE relationships

What You Need

• 6–8 years of direct experience in partnership/alliance roles within the cloud ecosystem

• Demonstrated track record of closing multiple deals through Google Cloud, AWS, or Azure partner

networks

• Established relationships with FSRs and Account Executives at one or more hyperscalers

• Strong understanding of co-sell motions, deal registration, and partner-sourced pipeline management

• Ability to advise leadership on partnership-led go-to-market strategy, not just execute existing

programs

• Strong sales acumen and comfort owning revenue-linked outcomes

• Excellent relationship-building and stakeholder communication skills

Nice to Have

• Experience working with Partner Development Managers/Executives in AI-first partner ecosystems

like Anthropic and OpenAI

• Experience with partner certification programs (Anthropic Claude Partner Network, AWS APN, Azure,

GCP)

Who You Are

• A relationship-first operator who can open doors within hyperscaler sales teams

• Commercially minded — you think in terms of pipeline, deal velocity, and closed revenue

• A strategic thinker who can shape how the company approaches partnership-led sales, not just follow

a playbook

• Comfortable operating with high autonomy and ownership of outcomes

Skills: Partner Sales, Co-sell, Channel Partnerships, Google Cloud Partner Network, AWS Partner Network,

Microsoft Azure Partner Network, Deal Registration, Pipeline Management, Strategic Alliances, GTM

Strategy

TECHJAYS

Position: Senior Database Engineer / DBA

Experience: 7+ Years

Location: Coimbatore / Hybrid (Remote option available)

Employment Type: Contract

Joining: Immediate or within 30 days preferred

Core Focus: Microsoft SQL Server Administration, Always On Availability Groups, Performance Tuning, Database Security, Disaster Recovery, Production Database Operations, High Availability, and Multi-Terabyte Database Management.

Tools & Platforms: Microsoft SQL Server (HA / Clustered), Always On Availability Groups (AGs), TDE & Auditing, T-SQL, Partitioning & Archiving, PowerShell, Snowflake / Redshift / AWS Aurora (Nice to Have).

About the Role

We are looking for a Senior Database Engineer / DBA to own a large, multi-terabyte Microsoft SQL Server environment running in a highly available, clustered configuration.This is a hands-on production database role supporting a live, customer-facing SaaS platform. The role focuses on maintaining database availability, performance, security, and reliability. This is not an analytics or reporting role.

The ideal candidate will have strong hands-on experience managing SQL Server databases in a 24x7 production environment, troubleshooting complex database issues, maintaining Always On Availability Groups, and ensuring business continuity through effective disaster recovery practices.

Key Responsibilities

1. Production Database Administration & High Availability

Own and maintain the production SQL Server environment in an Always On Availability Group configuration.Handle failover operations, synchronization delay troubleshooting, and read replica load management.Maintain database availability and ensure the stability of production database environments.Manage SQL Server alerts and provide on-call coverage for production database operations.

2. Performance Tuning & Incident Management

Lead incident response and root cause analysis for production database issues.Troubleshoot query plan regressions, TempDB contention, deadlocks, and blocking issues.Perform index and statistics maintenance to ensure optimal database performance.Review developers' T-SQL queries and schema changes before deployment. Advise developers on table design, indexing strategies, and database performance optimization.

3. Database Security & Compliance

Maintain database security through Transparent Data Encryption (TDE), auditing, and certificate and key rotation.Monitor anomalous database access patterns and ensure appropriate security controls.

Handle confidential or legally sensitive data requests following established processes.Maintain database security standards and support compliance requirements.

4. Database Maintenance & Capacity Planning

Perform quarterly cumulative update patching across database environments.Manage partitioning and archiving on multi-terabyte databases without impacting production performance.

Own capacity planning for storage, CPU, and memory.Manage recurring environment refreshes across staging, development, and QA environments.Ensure production maintenance activities are performed safely with minimal downtime.

5. Disaster Recovery & Database Migrations

Design, implement, and test disaster recovery strategies for SQL Server environments.Support customer instance migrations between regions, including database preparation and validation.

Perform regular DR testing and ensure database recovery readiness. Manage large-scale database migrations while maintaining availability and data integrity.

6. Production Operations & Support

Provide on-call, weekend maintenance, and after-hours support as required.Maintain clear documentation of database changes, incidents, and recovery procedures.Work closely with engineering teams to ensure reliable database operations.Ensure production database changes follow established change control and operational procedures.

Must-Have Requirements

• 7+ years of hands-on Microsoft SQL Server DBA experience in a 24x7 production environment. SQL development experience alone is not sufficient.
• 3+ years of direct experience with Always On Availability Groups, including failover handling and synchronization delay troubleshooting.
• Experience managing multi-terabyte production databases, including partitioning, archiving, and index and statistics maintenance without blocking production.
• Experience leading incident response and root cause analysis for production database issues.
• Strong experience with database security practices, including TDE, auditing, certificate rotation, and key management.
• Hands-on experience with SQL Server performance tuning, query optimization, and production troubleshooting.
• Experience designing and testing disaster recovery strategies.
• English fluency sufficient for real-time incident communication, with meaningful business-hours overlap with Pacific time.
• Nice-to-Have Skills
• Experience supporting a SaaS CRM or similarly high-transaction-volume application.
• Exposure to Snowflake, Redshift, or AWS Aurora alongside transactional SQL Server work.
• Experience with customer instance migrations or similar large-scale data movement projects.
• Experience in SOC 2, HIPAA, or PCI-regulated environments.
• Comfort handling legally sensitive or confidential data requests as part of a defined process.

What We're Looking For

Strong Ownership: Takes responsibility for maintaining large, multi-terabyte production databases and ensuring their availability and reliability.

Technical Expertise: Demonstrates deep hands-on knowledge of SQL Server administration, Always On Availability Groups, performance tuning, and disaster recovery.

Incident Management: Maintains a calm, structured approach during production incidents and takes ownership of root cause analysis and preventive actions.

Attention to Detail: Follows disciplined change control, documentation, database security, and maintenance practices.

Clear Communication: Communicates effectively with developers, engineering teams, and stakeholders during live production incidents.

Operational Excellence: Understands the importance of maintaining production databases with minimal downtime and without impacting customer-facing applications.

Execution-Focused Mindset: Comfortable managing day-to-day database administration, on-call support, and hands-on production operations.

What We Offer

• Flexible work environment with Coimbatore office, hybrid, and remote options.
• Paid holidays and flexible time off.
• Medical insurance coverage of up to ₹4 lakh per person for self and family.
• Opportunities to support production infrastructure for global clients.
• A culture that values clarity, integrity, accountability, and continuous growth.

TECHJAYS

Lead – Infrastructure Security & Release Operations

Position: Lead – Infrastructure Security & Release Operations

Experience: 8+ Years

Location: Coimbatore / Hybrid (Remote option available)

Joining: Immediate or within 30 days preferred

Core Focus: Production Release Management, Change Control, Security Operations, SOC 2 Compliance, Audit Evidence, Identity & Access Management.

Tools & Platforms: Octopus Deploy, TeamCity, AWS (IAM, Security Groups, CloudTrail), Status Page, Endpoint Security Tools, GRC Platforms (Vanta, Drata, or similar).

About the Role

We are looking for a senior, execution-focused professional to own production release management, change control, and day-to-day security and compliance operations.

This role focuses on ensuring production changes are deployed safely, maintaining accurate SOC 2 audit evidence, managing security operations, and enforcing disciplined access controls.

The ideal candidate will bring hands-on experience managing production deployment pipelines, coordinating change approvals, supporting external audits, and maintaining security and compliance processes in a production environment.

This is a hands-on execution role. Strategic roadmaps, architecture review boards, and cross-company leadership responsibilities remain with the existing leadership team and are outside the scope of this position.

Key Responsibilities

1. Production Release & Deployment Management

• Own production release and deployment pipelines using Octopus Deploy and TeamCity.
• Implement and maintain zero-downtime deployment practices and rollback procedures.
• Troubleshoot failed or stuck deployments and coordinate timely resolution.
• Approve production changes, hotfixes, and feature toggle changes.
• Coordinate maintenance windows and communicate planned changes to customers through the status page.

2. Security, Compliance & Audit Management

• Own SOC 2 change management processes and maintain complete, audit-ready evidence.
• Work directly with external auditors throughout SOC 2, HIPAA, PCI, or equivalent audit cycles.
• Track vulnerability remediation, security patches, and corrective actions.
• Manage endpoint security tooling and triage externally reported vulnerabilities.
• Support customer security questionnaires and security-related sections of RFPs.

3. Identity & Access Management

• Administer identity and access management processes, including access reviews and MFA enforcement.
• Manage privileged access controls and production access permissions.
• Grant, review, and revoke access to databases, VPNs, and deployment tools.
• Maintain appropriate access records and supporting compliance evidence.

4. Operational Support

• Manage infrastructure and access-related tickets requiring change approval or production access.
• Ensure production changes follow established approval and documentation procedures.
• Provide occasional on-call and after-hours support when required for production operations.
• Maintain clear documentation of releases, approvals, incidents, and security activities.

Must-Have Requirements

• 8+ years of overall infrastructure or release engineering experience.
• 5+ years of direct ownership of production release and deployment pipelines, including rollback procedures.
• 5+ years of ownership of SOC 2 or equivalent compliance change management and audit evidence processes.
• 5+ years of hands-on security operations experience.
• Practical experience administering IAM, including access reviews and privileged access controls.
• Experience supporting customer-facing security questionnaires and RFP security sections.
• Direct experience working with external auditors through at least one complete audit cycle.

Nice-to-Have Skills

• AWS security experience, particularly IAM, security groups, and CloudTrail.
• Familiarity with vulnerability disclosure platforms such as HackerOne or Bugcrowd.
• Experience coordinating third-party penetration tests.
• Familiarity with GRC and compliance platforms such as Vanta, Drata, or similar tools.
• Experience with customer trust and security review platforms such as Conveyor or CSA STAR.
• Previous experience working at a SaaS company serving regulated industries.

What We're Looking For

• Strong ownership: Takes responsibility for production releases, security operations, and compliance evidence.
• Sound judgment: Willing to stop or reject a production change that does not meet the required standards and explain the decision clearly.
• Incident management: Maintains a calm, structured approach when deployments fail or production incidents occur.
• Clear communication: Communicates effectively with engineering teams, external auditors, and customer security stakeholders.
• Attention to detail: Maintains accurate documentation, access records, approvals, and audit evidence.
• Execution-focused mindset: Comfortable managing day-to-day operational responsibilities without relying on strategic leadership duties.

What We Offer

• Flexible work environment with Coimbatore office, hybrid, and remote options.
• Paid holidays and flexible time off.
• Medical insurance coverage of up to ₹4 lakh per person for self and family.
• Opportunities to support production infrastructure and security operations for global clients.
• A culture that values clarity, integrity, accountability, and continuous growth.

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.
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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.