We are seeking a hands-on Senior Technical Lead with extensive experience in Generative AI and Agentic AI. This role requires deep expertise in Microsoft Azure AI services, multi-agent frameworks, LLM orchestration, Retrieval-Augmented Generation (RAG), Python, APIs, and cloud-native engineering.

The primary focus will be on translating architectural concepts into robust technical designs and production-ready solutions. You will lead complex development initiatives, mentor Technical Leads and developers, and uphold quality standards throughout the Software Development Life Cycle (SDLC).

Lead the design and development of advanced GenAI and Agentic AI solutions utilizing Azure OpenAI, Azure AI Foundry, Azure Agent Service, Microsoft Agent Framework, and LangGraph.

Design sophisticated multi-agent workflows encompassing planning, reasoning, state management, memory, tool invocation, human oversight, checkpoints, and robust failure recovery mechanisms.

Develop enterprise-grade RAG solutions leveraging Azure AI Search, vector databases, Cosmos DB, PostgreSQL with pgvector, and Redis.

Define and implement comprehensive prompt pipelines, embedding strategies, retrieval mechanisms, context management, tool integrations, safety guardrails, and model evaluation protocols.

Transform high-level architectures into detailed low-level designs, component specifications, API contracts, data flow diagrams, and actionable implementation plans.

Spearhead Python development using FastAPI or Django, incorporating asynchronous programming, robust API design, and microservices architecture.

Build and deploy solutions efficiently using Docker, AKS, Azure Functions, App Service, API Management, Event Grid, and Service Bus.

Implement and manage CI/CD pipelines through Azure DevOps or GitHub Actions, ensuring automated testing and stringent quality controls.

Design and enforce secure solutions employing authentication, authorization, managed identities, Key Vault, private networking, and content safety measures.

Ensure the scalability, performance, security, resiliency, observability, and cost-effectiveness of Azure deployments.

Conduct thorough design and code reviews, lead production troubleshooting efforts, perform root cause analysis, and optimize system performance.

Provide technical guidance and mentorship to Technical Leads and developers throughout the design, development, testing, deployment, and production support phases.

Collaborate effectively with cross-functional teams including architects, QA, DevOps, security, data, product, and integration specialists to manage technical interdependencies.

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

7 to 10 years of professional software engineering experience.

Extensive hands-on experience in AI, GenAI, Agentic AI, or cloud-native solutions deployed on Microsoft Azure.

Proven expertise with Azure OpenAI, Azure AI Foundry, Azure Agent Service, Microsoft Agent Framework, LangGraph, and Azure AI Search.

Significant experience in RAG implementation, embeddings, vector retrieval techniques, prompt engineering, context management, model evaluation, and AI guardrails.

Strong understanding of multi-agent orchestration, state management, memory patterns, tool calling capabilities, human review workflows, and failure recovery strategies.

Advanced proficiency in Python development with FastAPI or Django, extensive API design experience, asynchronous programming, and microservices development.

Experience with data technologies including Cosmos DB, PostgreSQL, pgvector, Redis, and deployment on AKS, Azure Functions, App Service, and API Management.

Familiarity with containerization (Docker), Kubernetes, Git, CI/CD practices, automated testing frameworks, observability tools, and production support methodologies.

Solid knowledge of Azure security best practices, managed identities, Key Vault usage, scalability principles, resiliency patterns, and Azure cost optimization.

Demonstrated experience leading development teams or multiple workstreams, including technical estimation, risk management, and release governance.