🚀 GenAI Engineer | Agentic RAG Systems | LLM Infrastructure

Building production-grade AI systems with LangGraph, FastAPI, and hybrid retrieval at scale.

• 🧑‍💻 AI/ML Engineer with 2+ years building production GenAI systems
• ⚙️ Designed and deployed Agentic RAG systems at scale
• ⚡ Built systems handling millions of documents with low-latency retrieval
• 🧠 Specialized in LLM orchestration, hybrid retrieval, and multi-agent systems
• 🚀 Building a production-grade GenAI DocQA platform (LangGraph + RAGAS + LLM routing)

LangGraph • LangChain • RAG • CRAG • RAGAS • LangSmith Hybrid Search (BM25 + Vector + RRF) • LLM Routing

FastAPI (async) • REST APIs • Microservices

PostgreSQL • pgvector • Qdrant • Redis • MongoDB

Docker • AWS • Kafka

• Built 13-phase production-grade system (5 phases complete)
• Hybrid retrieval (BM25 + vector + RRF) → +15–20% precision
• 10-node LangGraph agent with CRAG + self-correction loop
• Multi-provider LLM routing (Groq, OpenAI, Anthropic, Gemini)
• RAGAS evaluation: Faithfulness, Answer Relevancy, Context Recall

• Designed system handling millions of documents with low-latency responses
• Implemented multi-agent workflows for complex query reasoning
• Built tool-augmented retrieval pipelines with iterative refinement

• 💼 LinkedIn: https://www.linkedin.com/in/digvijay-singh-rajput
• 💻 GitHub: https://github.com/digvijaysingh21

✨ Building real-world GenAI systems that are fast, scalable, and reliable.