Pawan Kaur

I’m a GenAI developer specializing in LLM-powered systems, end-to-end RAG pipelines, and Python backend development. I focus on building intelligent, production-ready solutions with agentic workflows, semantic search, and clean API-driven architectures.

In my projects, I’ve engineered LangGraph-based agentic assistants with stateful orchestration, conditional routing, and multi-step pipelines for resume analysis and job matching. I also built RAG systems that handle PDF ingestion, chunking, embedding generation, similarity retrieval, and LLM-based answer synthesis—using fully offline inference.

I design backends with separation of concerns and the single responsibility principle to keep services modular and maintainable. I’ve implemented FastAPI and Flask REST APIs with structured document handling, automated Swagger documentation, and deployment for production access.

Beyond core LLM/RAG work, I enjoy creating practical applications that apply AI to real problems, like contextual document intelligence and phishing URL risk analysis. My goal is to keep iterating toward reliable, scalable AI experiences that teams can deploy with confidence.