Key Responsibilities 1. Implement AI solutions. 2. Build and manage agent orchestration services (multi-agent workflows, tool invocation, state management). 3. Knowledge in MCP, A2A and other new protocols 4. Deploy and manage LLM integrations (OpenAI, embeddings, fine-tuned models). 5. Design & Deploy Custom Document Intelligence Models 6. Implement RAG pipelines using AI Search, vector databases, and storage. 7. Design secure APIs, authentication, authorization, and secrets management. Required Skills & Experience 1. Deep expertise in App Services, Document Intelligence, AI Search, Open AI Foundry. 2. Strong understanding of LLMs, embeddings, RAG, agentic architectures, Agentic AI (Hallucination, MCP, Agent to Agent Communication) 3. OCR Tools (Doc Intelligence / John Snow Labs) 4. High Proficiency in Python 5. Working experience with LangGraph Good to Have 1. Experience with infrastructure-as-code (Bicep, Terraform). 2. Knowledge on compliance and data governance for AI systems. 3. Prompt Engineering
