I will develop agentic rag chatbot applications

Full Stack & AI Engineer

I specialize in building agentic RAG systems using LangChain, LlamaIndex, pydantic-ai, OpenAI, and vector store designed to deliver context-aware, multi-step reasoning pipelines that power enterprise-grade AI applications.

Agentic RAG Development

• Multi-agent orchestration
• Query routing, re-ranking, and hybrid retrieval pipelines
• Self-correcting and reflexion-based RAG agents trained on your proprietary data
• Context-aware, multilingual knowledge bases with semantic chunking strategies

Smart Data & Retrieval Integration

• Vector store setup and optimization: Pinecone, Weaviate, ChromaDB, FAISS, postgres
• Structured + unstructured data ingestion from PDFs, databases, APIs, and web sources, excels, csv
• Multi-index retrieval with metadata filtering and dynamic context injection
• n8n, Zapier, and custom API connectors for automated knowledge pipeline refresh

AI & Automation Expertise

• RAG evaluation frameworks: RAGAS, TruLens, and custom metrics dashboards
• End-to-end deployment on AWS, GCP, or Azure