CSE '28 @ IIIT Dharwad. I build backend systems that hold up under load.
- ⚡ Built a distributed reservation ledger — Saga pattern, Redis→DynamoDB fallback, 229 RPS @ p95 315ms
- 🧠 Shipped an AI SQL optimizer that rewrites queries using hypothetical index simulation (Querion)
- 🤖 Built an AI career coach with LLM-driven mock interviews and ATS scoring (Beacon-AI)
- 🌐 Comfortable across the stack: from AWS infra to React UIs
- 📖 I read production postmortems for fun
- 💼 Full-Stack Development intern @ CodeAlpha
- 📫 Always open to connecting — reach me on LinkedIn
A high-concurrency, event-driven inventory reservation and transaction ledger engine. Implements distributed transactions via the Saga pattern, Redis-to-DynamoDB fallback for fault tolerance, Token-Bucket rate limiting, and structured JSON request tracing. Tech: AWS Step Functions • DynamoDB • Redis • TypeScript • Docker
A full-stack AI career coach that conducts realistic mock interviews and scores resumes for ATS compatibility. Uses LangChain-orchestrated Gemini prompts for personalized skill-gap roadmaps, Inngest for async background jobs, and Clerk for authentication. Tech: LangChain • Gemini AI • Next.js • Neon Postgres • Clerk • Inngest
An AI-assisted SQL optimizer that parses queries into an AST using sqlglot and simulates hypothetical indexes with HypoPG. Streams optimization reasoning via SSE, renders visual query plans with D3.js, and shows AI-suggested rewrites in a Monaco diff viewer. Tech: sqlglot • HypoPG • Gemini AI • Next.js • FastAPI • PostgreSQL • D3.js
📍 Shivamogga, Karnataka, India