NMP
Nitinkumar Patel
Available

NitinkumarPatel

Staff AI/LLM Engineer

Staff AI/LLM Engineer with 12+ years building high-scale distributed systems and production Generative AI (GenAI) platforms. Built and led teams of 5+ engineers to ship Retrieval-Augmented Generation (RAG) pipelines, multi-agent workflows, and full-stack SaaS products achieving 95% accuracy, 20% cost reduction, and 99.99% availability. Driven by a belief that stable, well-architected systems free teams to move fast and think big, not worry about what might break. Actively seeking Staff AI/LLM Engineer roles (Remote-first).

Why this work matters

AI that works in production,
not just in demos.

I build GenAI products, RAG pipelines, and agentic workflows. The focus is always on reliability, real impact, and code that holds up under production load.

Why I do this

Good engineering should give teams the stability to stop worrying and just build.

Most AI projects fail not because the model was wrong, but because the system around it wasn't built to last. I care about the parts that aren't glamorous: reliability, observability, and making sure things still work six months after launch.

How I help

  • Design AI systems that hold up in production
  • Build RAG pipelines and agentic workflows that actually solve the problem
  • Ship full-stack AI products from idea to deployed
  • Add reliability, observability, and speed where it's missing
  • Take an AI idea and turn it into something real

Featured work

Projects

MarketMind

Agentic multi-tool research assistant

MarketMind is an agentic multi-tool research assistant built with LangGraph and OpenAI tool-calling, demonstrating autonomous web research, summarization, and reporting.

LangGraph · OpenAI

View on GitHub

Nitin’s Digital twin GenAI Chatbot

A GenAI Chatbot designed to simulate a digital twin, providing interactive and personalized user experiences.

Live Demo

Multi Locations Route Planner

A route planner application that optimizes travel paths across multiple locations, enhancing logistical efficiency.

Live Demo

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