Generative AI Engineer with hands-on experience building production-grade AI solutions, including a multi-agent RAG system using LangGraph, LangChain, Google Gemini, FastAPI, ChromaDB, and Docker. Proficient in LLM API integration, prompt engineering, semantic search, and agentic workflows. Currently working at Capgemini with 1.6+ years of enterprise experience.
Multi-Agent Document Intelligence System for Enterprise Operations
A production-grade agentic RAG system built using real retail enterprise domain knowledge from JLP/Waitrose.
User Query → FastAPI → LangGraph Router → Policy / Compliance / Incident Agent
↓
RAG (ChromaDB + Gemini Embeddings)
↓
Grounded Answer → Streamlit UI
Stack:
LangGraph Multi-Agent System with ReAct Pattern
A three-agent system (Researcher → Reasoner → Responder) with stateful graph orchestration, iterative reasoning, and external search integration.
Stack:
Gen AI & LLM
AI Frameworks & Platforms
Vector Databases & Retrieval
Backend Development
Programming & Databases
DevOps & Cloud
- 🥇 Oracle Cloud Infrastructure 2025 AI Foundations Associate — Oracle
- 📘 Microsoft Azure AI Fundamentals (AI-900) — Microsoft (In Progress)
I'm actively looking for AI Engineer / Gen AI Developer roles at product companies, startups, and GCCs.
If you're building something interesting in the AI space — let's talk!
