Rahul Jha is an experienced AI Python developer with over 5 years of expertise in developing intelligent backend architectures. He specializes in integrating AI technologies and building scalable APIs. His projects include real-time chat platforms and AI-powered question-answering systems, showcasing his ability to deliver high-performance solutions. Rahul is adept at collaborating with cross-functional teams and has a proven track record of deploying production-ready applications.
Built scalable APIs for AI-driven workflows
Integrated multi-model LLMs for intelligent features
Deployed platforms on DigitalOcean ensuring high availability
Collaborated with frontend teams to enhance user experience
Developed production-ready applications for thousands of users
Scaled the Bind AI platform to thousands of users
Contributed to Forzza, which has 1,10,000+ live players
Implemented vector search capabilities using Qdrant
Overview: Bind AI is a production-ready, multimodal AI platform built for real-time chat, semantic search, and code execution across multiple LLMs. Responsibilities: I worked as the primary backend developer for its Copilot system, built and maintained scalable Flask APIs, integrated LangChain, LangGraph, and LiteLLM for multi-model orchestration, and implemented Qdrant for vector search capabilities. I also set up Stripe billing and deployed the platform on DigitalOcean.
Key outcomes:
Scaled the platform to thousands of users
Contributed to a successful AppSumo launch
Overview: Instant Assist is an AI-powered real-time question-answering platform. Responsibilities: I developed multi-agent LLM workflows that enable dynamic task routing, semantic search, and contextual memory using vector databases. The system intelligently handles complex queries and generates precise responses.
Overview: Forzza is an igaming project where players can place bets on sports feeds and casinos. Responsibilities: I built the backend using Django REST API, integrated DynamoDB and Postgres for real-time data, and ensured scalability for over 1,10,000 live players.
Key outcomes:
Part of the scaling team for 1,10,000+ live players
Overview: KodeKloud project is developed on Flask and AngularJS. Responsibilities: I developed REST APIs using Flask and managed MongoDB connections.
Overview: 2Key is developed using multiple technologies. Responsibilities: I developed backend scripts and REST APIs using Django REST framework.
Rahul Jha
Python AIML