About Me
Backend engineer with 6 months of industry internship experience and extensive project experience building scalable REST APIs, SaaS platforms, and Retrieval-Augmented Generation (RAG) systems using Python, Django, FastAPI, and Django REST Framework. Built AI-powered backend applications including clinical and legal RAG systems, a multi-tenant SaaS platform, and real-time event-driven services using Celery and WebSockets. Passionate about AI-native software development and production-ready backend systems; seeking Backend or GenAI Engineering roles.
Skills & Technologies
Work Experience
Django Fullstack Developer Intern
Developed backend for a document upload and print-request fulfillment platform, building REST APIs for file handling, order queuing, and admin print-queue management using Django and DRF. Designed MySQL schemas and optimized ORM indexing, reducing query times by 35%. Implemented JWT authentication and role-based access control for multiple user roles.
Projects
MedRAG — AI Clinical Assistant RAG pipeline
Built a Retrieval-Augmented Generation pipeline ingesting medical PDFs, chunking documents, and embedding them into ChromaDB for source-cited clinical query answering. Implemented hybrid retrieval to improve answer relevance and integrated GPT-4o with safety disclaimers for clinical use. Exposed system via FastAPI backend with streaming responses and React chat UI.
StockPro — Stock Calls Real-time SaaS alert platform
Aggregated buy/sell calls from multiple analyst sources into a filterable feed and deployed real-time notification architecture using Django Channels and Celery Beat for asynchronous event processing, WebSocket communication, and Telegram notifications. Built signal-performance tracker supporting role-based access with win-rate analytics.
Studypedia — Multi-Tenant SaaS Learning Platform
Converted internship project into a multi-tenant SaaS platform with isolated data per institution, custom branding, and role-managed portals. Integrated Razorpay payment gateway with secure webhooks and idempotency keys. Offloaded email and PDF generation to Celery and Redis, maintaining core API responses under 200ms and designed subscription tiers with API feature gating.
LawRAG — Legal Domain RAG Pipeline
Designed a RAG system over Indian Penal Code and Supreme Court judgments scraping multiple legal sources. Uses Pinecone vector store, hybrid retrieval, Hugging Face Inference API for embeddings and generation, designed to surface case precedents alongside plain-language legal explanations. Retrieval pipeline and scraping layer in progress, not yet deployed.
Education
B.Tech
Computer Engineering