Overview

We are looking for a Senior AI Lead – Agentic & GenAI with strong expertise in Azure AI Foundry to own an Agentic AI engineering POD and lead the design, development, and deployment of enterprise-grade Generative AI and multi-agent solutions. The candidate will translate functional requirements into technical workstreams, drive delivery across engineering PODs, contribute hands-on code, establish AI engineering standards, and mentor development teams.

Key Responsibilities

• Own the Agentic AI POD and deliver identified features in collaboration with Data, UI/UX, Infrastructure, and other PODs.
• Translate functional requirements into technical tasks, architecture decisions, and executable delivery plans.
• Design and develop multi-agent solutions using Azure AI Foundry and Azure AI Agent Service.
• Build AI agents and implement agent orchestration, workflow management, memory, and state-management components.
• Design and implement RAG solutions using Azure AI Search and vector stores.
• Develop prompt engineering, tool calling, function calling, and agent collaboration frameworks.
• Implement observability, distributed tracing, evaluation, and AgentOps capabilities.
• Develop Human-in-the-Loop workflows and agent recovery mechanisms.
• Contribute directly to development, conduct code reviews, and mentor engineering teams.
• Troubleshoot performance, response quality, hallucination, model/agent drift, and orchestration issues.
• Define and implement AI governance, security, compliance, and responsible AI controls.
• Lead the development and deployment of production-grade Generative AI solutions.

Mandatory Requirements

• 15+ years of overall professional experience.
• 5+ years of hands-on Architecture experience.
• 3+ years of hands-on Generative AI / Agentic AI development.
• Proven experience developing and deploying enterprise-grade production GenAI solutions.
• Strong hands-on expertise in Python.
• Hands-on project experience with Azure AI Foundry.
• Hands-on experience with Azure OpenAI and LLM solution deployment.
• Hands-on experience implementing RAG/search solutions using Azure AI Search.
• Hands-on experience with Azure AI Agent Service.
• Production-scale multi-agent systems covering orchestration, workflow, memory, and state management.
• Experience with AI governance, security, observability, evaluation, and Human-in-the-Loop capabilities.
• Hands-on exposure to Azure, AWS, or GCP, with Azure strongly preferred.
• MS/M.Tech in Computer Science, Information Systems, Computer Engineering, or equivalent relevant qualification.

Required Technical Skills

• AI / GenAI: Generative AI, LLM applications, Agentic AI, Multi-Agent Systems, RAG, Prompt Engineering, Tool Calling, Function Calling.
• Microsoft AI Stack: Azure AI Foundry, Azure OpenAI, Azure AI Search, Azure AI Agent Service, Document Intelligence, Azure AI Services.
• AI Frameworks: Semantic Kernel, LangGraph, LangChain, AutoGen, MCP.
• Agent Engineering: Agent building, orchestration, workflow management, memory, state management, recovery, Human-in-the-Loop.
• AI Quality & Operations: Observability, tracing, evaluation, AgentOps, hallucination mitigation, performance/quality troubleshooting, and drift management.
• Architecture: REST APIs, Microservices, Event-Driven Architecture, Distributed Systems, Scalable Enterprise Architecture.
• Data & Storage: PostgreSQL, Cosmos DB, Redis, Vector Stores, Enterprise Retrieval Architectures.
• Cloud & Deployment: Azure preferred; AWS/GCP acceptable. Production AI deployment experience is essential.
• Engineering Practices: Code development, code reviews, technical documentation, Agile delivery, and mentoring.
• Governance & Security: AI governance, security, compliance, responsible AI controls, and enterprise deployment standards.

Ideal Candidate

A hands-on AI Architect / Technical Lead combining deep software architecture expertise with recent production experience in GenAI and Agentic AI. The candidate should be capable of moving from functional requirements to technical architecture, guiding an engineering POD, making pragmatic platform decisions, and personally contributing to implementation while ensuring enterprise-grade security, governance, observability, and AI quality.

Engagement Details

• Location: Bangalore
• Work Mode: Onsite
• Shift: Day Shift
• Experience: 15+ Years
• Core Technology: Azure AI Foundry / Azure OpenAI / Agentic AI / GenAI
• Contract: Contract engagement