Amitabh Anmol Pain

I build robust, scalable server-side systems and APIs that power seamless digital experiences, with a growing focus on cloud architecture for backend systems.

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Amitabh Anmol Pain

About Me

I am a Computer Science undergraduate currently in my third year, with a strong passion for coding and building scalable backend systems. I actively develop projects and contribute to GitHub, and I occasionally participate in open-source initiatives to collaborate and learn from the developer community.

I have taken part in multiple hackathons, including the Bolt Vibe Coding Hackathon and Walmart Sparkathon, and have been a finalist in several competitive hackathons. Currently, I am focusing on learning cloud architecture for backend systems and enjoy collaborating on impactful open-source projects.

Quick Stats

  • LocationRemote / India
  • StatusCS Undergraduate
  • FocusBackend & AI

Skills

HTML
HTML
CSS
CSS
JavaScript
JavaScript
Node.js
Node.js
Express
Express
Flask
Flask
Fast API
Fast API
Docker
Docker
PostgreSQL
PostgreSQL
Redis
Redis
Supabase
Supabase
TypeScript
TypeScript
React
React
Python
Python
Next.js
Next.js
MongoDB
MongoDB
C++
C++
Git
Git
SQL
SQL
Tailwind
Tailwind
Postman
Postman
Google ADK
Google ADK

Work Experience

Hacktoberfest 2025 logo

Open Source Contributor

Hacktoberfest 2025

October 2025 - November 2025

Participated in Hacktoberfest 2025, contributing to open-source projects worldwide. Made 10+ pull requests and merge requests across various repositories, focusing on backend development, feature implementation, and bug fixes for maintainers' repositories.

Key Contributions:

  • Successfully merged 10+ PRs/MRs across multiple open-source projects, demonstrating versatility in different tech stacks.
  • Contributed to backend development, implementing new features and API endpoints for production applications.
  • Fixed critical bugs and improved code quality in maintainers' repositories, enhancing overall project stability.
  • Collaborated with global developers, following best practices for code review and documentation.
Bolt Hackathon logo

Bolt World's Largest Vibe Coding Hackathon

Bolt Hackathon

June 2025 - August 2025

Built an app for detecting fake jobs using machine learning models including regression modeling and random forest. Developed with Next.js, Tailwind CSS, and GSAP for smooth animations.

Key Contributions:

  • Engineered an automated system to detect fake job listings using pattern recognition and verification algorithms.
  • Focused on creating a safer environment for job seekers within major job portals.

Projects

Restaurant Management & Analysis

Restaurant Management & Analysis

FlaskReactMongoDB

A full-stack web application for restaurant owners to analyze customer reviews, monitor sales trends, reduce food wastage, and boost revenue. Built with React, Flask, and MongoDB with interactive dashboards using Matplotlib and Seaborn.

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Real-Time Chat Application

Real-Time Chat Application

MERNMongoDBRedis

A full-stack MERN chat application with real-time messaging using WebSockets. MongoDB serves as the primary database, while Redis is used for caching and efficient message handling.

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Ecofinds - Student Marketplace

Ecofinds - Student Marketplace

MERNMongoDBMarketplace

A smart MERN stack marketplace where students can buy and sell second-hand products at affordable prices with secure listings and smooth transaction management.

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React Native Hotel App

React Native Hotel App

React NativeDockerSupabase

A cross-platform mobile application built using React Native, Docker, and Supabase for browsing and booking hotels with real-time database integration.

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Real Estate Multi-Agent AI

Real Estate Multi-Agent AI

Google ADKAI AgentsReal Estate

An intelligent multi-agent AI system for real estate built using Google ADK to automate property analysis, recommendations, and market insights.

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Consumer Justice AI Agent

Consumer Justice AI Agent

Google ADKAI AgentsConsumer Protection

A smart AI agent that analyzes user-reported consumer fraud cases, determines applicability under consumer protection laws, and guides users through complaint filing processes.

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