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PROJECT / CASE STUDY

AI Resume Roaster.

AI-powered resume analysis with actionable feedback, version history, and secure user profiles.

ReactNode.jsExpressMongoDBTailwind CSSJWTGoogle Gemini APIPDF ProcessingAPI Rate Limiting
Live project Source code
AI Resume Roaster project cover: AI-powered resume feedback with Gemini and the MERN stack

Overview

A personal project built between August and September 2026. AI Resume Roaster uses the Google Gemini API to parse resumes in under three seconds and generate more than 15 actionable feedback points per scan.

Backend and data

I designed a MongoDB schema to manage user profiles, resume version histories, and analytics. The Node.js and Express backend includes strict input validation, custom error handling, secure JWT authentication, and API rate limiting.

Frontend and performance

The responsive React/Vite frontend uses Tailwind CSS, custom hooks, and the Context API. These optimizations reduced re-renders by approximately 30% and achieved a Lighthouse score above 95, as recorded in my resume.

Technical focus

  • Google Gemini API integration for actionable resume feedback
  • PDF processing and parsing
  • MongoDB schema design for profiles, histories, and analytics
  • Secure authentication, validation, and rate limiting
  • Responsive React interfaces and render optimization