Backend engineer focused on building scalable APIs, microservices, and distributed systems. I care about clean architecture, reliable message-driven workflows, and services that hold up under real load. On the side, I explore applied AI — RAG pipelines, semantic search, and LLM-backed tooling.

url-shortner Node.js RabbitMQ Redis JWT Railway

Production-grade URL shortener with async click analytics via RabbitMQ, Redis caching, JWT auth with token blocklist, and admin controls. Deployed on Railway.

Nodejs-Microservices-with-RabbitMQ Node.js RabbitMQ Express

Microservices architecture using RabbitMQ direct exchange for inter-service communication — decoupled, async, and independently deployable.

Paytm-Monorepo Next.js Node.js PostgreSQL Turborepo

Full-stack monorepo with shared code across frontend and backend. Payments flow built on top of Next.js + Node.js, backed by PostgreSQL.

E-Commerce-MERN MongoDB Express React Node.js

Real-time full-stack e-commerce application — product management, cart, orders, and user auth across a clean MERN stack.

LLM-search Python pgvector MLflow Airflow

Production-grade semantic search service using LLMs and pgvector. Includes experiment tracking with MLflow and pipeline orchestration via Airflow.

Conversational-RAG-QA-Chatbot Python LangChain Streamlit

Upload PDFs and chat with their content. Uses RAG with chat history and customizable prompts — built to explore retrieval-augmented generation end-to-end.

Languages

Backend

Messaging & Caching

Databases

Infra & Tools