Chirag Sen

I’m a Backend and GenAI Engineer focused on bridging Java engineering with Python-based LLM systems to ship reliable, observable AI backend services. I specialize in production-ready RAG pipelines and agentic workflows that can handle real enterprise complexity.

At LTIMindtree, I built an end-to-end RAG pipeline for an enterprise knowledge base, including document ingestion, semantic chunking, embeddings, FAISS vector storage, and grounded response synthesis. I also implemented agentic LangGraph workflows with stateful query routing, conditional retrieval fallback, and multi-step reasoning, and I added structured logging with correlation tracking to enable end-to-end observability.

Beyond LLM systems, I bring strong backend engineering fundamentals from building Spring Boot APIs with OAuth2/JWT, distributed components with Kafka and Redis, and production-grade rate limiting. My projects include an IDF Agent that reduced documentation turnaround by 75% using multi-agent LangGraph + RAG with retry/fallback/observability, a PolicyIQ HR assistant exposed via Spring Boot REST APIs, and infrastructure work like a distributed rate limiter and a Jenkins CI/CD automation platform.