Aman Sigroha

Built and deployed a production KYC verification system solo using FastAPI, OpenCV, InsightFace, and PaddleOCR, with zero external AI API costs, using a 3-tier architecture deployed on Railway, now live in the client's iOS and Android apps. Developed multi-step liveness detection with secure challenge verification, achieving 90%+ face-match accuracy in production.

Built core MVP features (auth, dashboard, profile, AI-driven roadmap generation) as one of two developers on a pre-seed team with no senior engineers, using Next.js, FastAPI, and PostgreSQL. Designed and implemented the database schema from scratch and prepared a pixel-perfect frontend for a platform connecting students and professionals with paid mentors.

Built a simplified Node.js, TypeScript, and MongoDB backend, parsing a 1,500-page Nausys API spec solo to offload traffic from the client's main system. Designed 50+ search filters and an automated data sync pipeline refreshing yacht data every 2 hours for real-time booking.

Fixed a poorly structured, AI-generated React.js codebase as the sole frontend intern, eliminating full-page re-renders on data changes. Refactored state management, debugged production issues, and shipped new features while integrating with the Java backend.

Grade: 8.09/10

Pursuing a B.Tech in Artificial Intelligence and Data Science with a CGPA of 8.09/10, expected to graduate in June 2027.