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sanjaykunta/README.md

Hi, I'm Sanjay Kunta

Senior Software Engineer transitioning into AI Engineering, with full-stack fintech experience and hands-on projects in Agentic AI, RAG, LangGraph, MCP, FastAPI, Java, Python, and cloud-native backend systems.

Focus Areas

  • Agentic AI systems with LangGraph and CrewAI
  • Retrieval-Augmented Generation with citations and verification
  • MCP-based tool integrations for AI agents
  • Backend APIs using FastAPI, Java, and Spring Boot
  • Testable, production-style engineering with CI, Docker, and clean architecture

Featured Projects

Multi-Agent Coding Assistant

LangGraph-based coding assistant that converts software requirements into design, implementation code, tests, and code review using RAG, MCP, FastAPI, and Gemini/Vertex AI.

Tech: Python, LangGraph, FastAPI, MCP, Gemini, RAG, Docker, pytest

DocuVerify RAG

Agentic RAG system that answers questions over documents using hybrid BM25/vector retrieval, source citations, verification, and self-correction.

Tech: Python, CrewAI, LangChain, BM25, OpenAI embeddings, Gemini, Gradio, pytest

Currently Building

  • Production-style AI engineering portfolio projects
  • Agentic AI systems with tool use and verification loops
  • Java + AI backend services for enterprise use cases

Connect

  • LinkedIn: add your LinkedIn URL
  • GitHub: github.com/sanjaykunta

Pinned Loading

  1. multi-agent-coding-assistant multi-agent-coding-assistant Public

    Multi-agent coding assistant using LangGraph, Vertex AI Gemini, embedding-based RAG, and MCP client/server tooling to generate implementation code, tests, and code reviews from software requirements.

    Python

  2. docuverify-rag docuverify-rag Public

    Built a Python agentic RAG pipeline with hybrid BM25/vector retrieval, source citations, verification, and self-correction to reduce unsupported AI answers.

    Python