Generative AI & Agentic Document Intelligence Architected an end-to-end Generative AI pipeline using transformer-based LLMs, enabling intelligent document categorization and context-aware semantic search across enterprise repositories Engineered agentic AI workflows with multi-step reasoning chains, implementing MCP (Model Context Protocol) and A2A (Agent-to-Agent) interaction patterns for autonomous document processing Deployed a hybrid RAG architecture combining FAISS vector similarity search with structured queries, improving LLM grounding and contextual retrieval accuracy by reducing irrelevant results Containerized and deployed scalable model inference pipelines using Docker on Azure Kubernetes Service (AKS), ensuring production-grade availability and horizontal scalability