🚀 Full Stack Developer | 🧠 Generative AI Engineer | 💻 Tech Blogger
Building production-grade RAG systems and scalable web applications

• 🔭 Currently building enterprise RAG systems with LangChain, ChromaDB, and FastAPI
• 🧠 Specialized in Generative AI — from RAG architecture to production deployment with guardrails
• 💼 Full-stack engineer with expertise in React, Node.js, MongoDB, and Python
• 🛡️ Passionate about AI safety, compliance, and production-ready systems
• ✍️ Writing about real-world dev tips and AI discoveries on Medium

Full-Stack GenAI System | Python | FastAPI | Streamlit | LangChain

Enterprise-grade RAG system for analyzing SEC 10-K financial documents with proven metrics:

• ✅ 0.81 RAGAS Score (Excellent - Production Ready) with quantitative evaluation
• ✅ Hybrid Retrieval - BM25 + semantic search with cross-encoder re-ranking
• ✅ Production Guardrails - PII detection, content filtering, compliance checking
• ✅ REST API & UI - FastAPI backend with OpenAPI docs + Streamlit interface
• ✅ Citation Validation - 0% hallucinations with source tracking
• ✅ Smart Parsing - Structure-aware document processing with table preservation

Tech Stack: LangChain, ChromaDB, Groq (Llama 3.3), RAGAS, Microsoft Presidio, FastAPI, Streamlit

Multi-Tenant RAG | Document Intelligence | Access Control

• 🧠 Advanced RAG Patterns - Multi-hop reasoning, adaptive retrieval, and query routing
• 🔐 AI Guardrails - PII detection, compliance checking, and safety frameworks
• 📊 RAG Evaluation - RAGAS metrics, hallucination detection, and quality benchmarking
• ⚛️ Advanced React Patterns - State management and performance optimization
• ☁️ Azure DevOps - CI/CD pipelines and cloud deployments

Backend & APIs

Frontend

Generative AI & RAG

Databases & Storage

• 🛡️ Building Production-Ready RAG Systems with Guardrails (Coming Soon)
• 🔍 Hybrid Search: Combining BM25 and Vector Embeddings (Coming Soon)
• 🧩 Disable React Developer Tool Extension
• 🧹 Best Practices I Learned from SonarQube

• 🎯 Built production-grade RAG system with 0.81 RAGAS score and zero hallucinations
• 🔐 Implemented AI guardrails (PII detection, content filtering, compliance checking)
• 📊 Achieved 30-40% cache hit rate optimization in RAG query system
• ⚡ Designed hybrid retrieval with semantic + keyword search and re-ranking
• 🚀 Deployed FastAPI backend with WebSocket streaming and OpenAPI documentation

• 💼 LinkedIn
• 📝 Blog
• 🐦 Twitter
• 📧 Email: sourabhgrover29@gmail.com

💡 Open to collaborating on GenAI projects and RAG system innovations!