Agentic AI Lead

Job Description – Agentic AI Technical Lead

Key Responsibilities

• Design and develop multi-agent AI solutions using LangGraph, Semantic Kernel, AutoGen, CrewAI, and LangChain.
• Build Agentic AI workflows with MCP, A2A, AG-UI, tool calling, memory, and Human-in-the-Loop (HITL) capabilities.
• Develop full-stack AI applications using React, Python, and TypeScript.
• Implement LLM integrations using OpenAI, Azure OpenAI, and Anthropic Claude.
• Design and implement RAG solutions using Azure AI Search, PostgreSQL pgvector, and Cosmos DB.
• Deploy and manage AI solutions on Azure AI Foundry, Azure OpenAI, Azure ML, and AKS.
• Build scalable cloud architectures using Azure Functions, Event Grid, Service Bus, Docker, Kubernetes, and Terraform.
• Implement REST APIs, microservices, CI/CD pipelines, and Infrastructure as Code.
• Ensure enterprise AI security, governance, observability, responsible AI, and data protection.
• Lead architecture decisions, mentor engineering teams, and drive AI-native engineering practices.

Required Qualifications

• 7+ years of software engineering experience, including 3+ years in AI/ML or LLM-based solutions.
• Strong hands-on experience developing production-grade Agentic AI and multi-agent systems.
• Expertise in LangGraph, Semantic Kernel, AutoGen, CrewAI, or LangChain.
• Working knowledge of MCP, A2A, AG-UI, and CodeAct patterns.
• Strong experience with OpenAI APIs, Claude APIs, RAG, prompt engineering, and LLM evaluation.
• Proficiency in Python, TypeScript, React, and REST API development.
• Strong Azure experience: Azure AI Foundry, Azure OpenAI, Azure ML, AKS, and Azure Functions.
• Experience with Docker, Kubernetes, Terraform, PostgreSQL, SQL Server, Cosmos DB, and MongoDB.
• Knowledge of OAuth 2.0, Azure IAM, RBAC, and Azure Key Vault.
• Strong technical leadership, architecture, and mentoring skills.

Good to Have

• Experience with Azure AI Agent Service, Databricks, MLflow, and document intelligence platforms.
• Knowledge of insurance domain workflows, particularly underwriting and submission processing.
• Azure certifications such as AI-102, DP-100, or AZ-305.
• Experience with AI-assisted development tools such as GitHub Copilot and autonomous coding agents.

Overall Experience: 7+ Years
Relevant AI/ML Experience: 3+ Years
Primary Focus: Agentic AI, Multi-Agent Architecture, Azure AI, LLM Engineering, and Full-Stack Development.