# Rakshan Shetty

> Full stack, backend and GenAI engineer. Builds web applications, REST APIs and AI agents, and maintains Baton and Elmory, two open-source tools for shipping software faster with AI coding agents.

Rakshan builds web applications end to end in React, Next.js, Node.js and Python, designs the APIs and data models behind them, and adds LLM features such as RAG pipelines and AI agents with LangChain, LangGraph and the Gemini and OpenAI APIs. Much of his recent work is AI-assisted engineering: running several AI coding agents in parallel, coordinating them so they don't overwrite each other, handing a plan from one agent to the next, and giving agents memory they can trust.

Contact: rakshanshetty2003@gmail.com. Based in Karnataka, India; open to remote work.

## Open source

- [Baton](https://baton-landing.vercel.app): Orchestration for AI coding agents. Claude Code plans and reviews while Cursor, Codex, Gemini and free models build in parallel: 10 to 15 agents on one codebase without conflicts, one shared knowledge base, team mode and one-click project setup. Built at a startup to fix testers' bugs in parallel with feature work. TypeScript, 641 tests, MIT. Case study: https://rakshan-shetty.netlify.app/project/12/baton. Source: https://github.com/Rakshan001/Baton-Multi-Agent-
- [Elmory](https://elmory.vercel.app): Evidence-checked memory for AI coding agents. Every fact quotes the code that proves it and is served only while that code still exists; when nothing holds, recall answers "I don't know". CLI and MCP server with nine tools. TypeScript on Node 24, SQLite full-text search, MIT, pre-release. Source: https://github.com/Rakshan001/elmory

## Skills

- Languages: TypeScript, JavaScript, Python, SQL, PHP, Java
- Frontend: React, Next.js, React Native, Redux, Tailwind CSS, server-side rendering
- Backend: Node.js, Express, Django, Flask, REST APIs, Server-Sent Events, JWT auth, RBAC
- GenAI: RAG, LangChain, LangGraph, LangSmith, Gemini API, OpenAI API, MCP, AI agents, multi-agent orchestration, embeddings, vector search
- Machine learning: TensorFlow, Keras, CNNs, scikit-learn, OpenCV, NLP
- Data and infrastructure: PostgreSQL, MongoDB, MySQL, SQLite, Redis, Docker, AWS (EC2, S3, SES), GitHub Actions, CI/CD

## Pages

- [Portfolio](https://rakshan-shetty.netlify.app/): experience, projects, skills and education
- [Elmory case study](https://rakshan-shetty.netlify.app/project/13/elmory)
- [Baton case study](https://rakshan-shetty.netlify.app/project/12/baton)
- [Resume (PDF)](https://rakshan-shetty.netlify.app/resume/Rakshan_Shetty_Resume.pdf)
- [GitHub](https://github.com/Rakshan001)
- [LinkedIn](https://linkedin.com/in/rakshan-shetty-953864225)