Full Stack Engineer with 4+ years of experience building AI-powered SaaS applications, scalable React frontends, Python services, and cloud-native systems.
π React β’ TypeScript β’ Next.js β’ Node.js β’ Python β’ AWS β’ AI β’ LLMs π Open to Global Opportunities
I'm a Full Stack Engineer with 4+ years of experience building scalable web applications, enterprise dashboards, AI-powered workflows, and cloud-native systems.
I enjoy solving real-world problems through modern web technologies, automation, and Large Language Models.
Currently exploring:
β’ Agentic AI β’ Multi-Agent Systems β’ Model Context Protocol (MCP) β’ RAG & Vector Databases β’ Distributed Systems
Production-grade, multi-tenant SaaS platform for QR-based review management and AI-powered sentiment analysis. ReviQR helps local businesses intelligently route customer feedback, convert positive experiences into public reviews, and privately capture negative feedback for resolution.
Highlights:
- π Smart QR routing with 4β5 star β Google/TripAdvisor and 1β3 star β private feedback flow
- π€ OpenAI-powered AI Review Assistant for contextual review generation
- π Real-time analytics for sentiment, NPS, branch performance, and feedback trends
- π Multi-tenant RBAC with JWT authentication, rate limiting, and salted IP hashing
- ποΈ Turborepo monorepo with separate web, API, database, and shared packages
- π Production deployment using Vercel, Railway, Supabase, Docker, and PostgreSQL
Tech: Next.js β’ React β’ TypeScript β’ Node.js β’ Express β’ PostgreSQL β’ Drizzle ORM β’ OpenAI β’ Redis β’ Docker β’ Turborepo β’ Vercel β’ Railway β’ Supabase
AI-powered YouTube knowledge base and RAG assistant that transforms YouTube videos into searchable, conversational knowledge bases. Users can provide a YouTube video, process its transcript, and interact with the content using semantic retrieval and LLM-powered Q&A.
Highlights:
- π₯ YouTube transcript extraction and document processing
- π§ RAG pipeline for context-aware question answering
- π Semantic search using FAISS vector embeddings
- π€ OpenAI-powered conversational Q&A
- β‘ FastAPI backend with React + Vite frontend
- π§© Recursive text splitting and retrieval pipeline for long-form video content
Tech: Python β’ FastAPI β’ React β’ Vite β’ LangChain β’ OpenAI β’ RAG β’ FAISS β’ Vector Embeddings β’ YouTube API
Open to collaborations.
Interested in AI, SaaS and DevTools.


