Software Engineer • Product Builder
I’m an engineer-at-heart who enjoys building useful things, building them well, and scaling them meaningfully.
My work spans consumer products, infrastructure products, GenAI, and 0→1 product journeys.
I care about clarity, utility, performance, taste, and empathy in both code and collaboration.
Currently pursuing my MS in Computer Science @ Northeastern, wherein I’m revisiting (and reinvesting in) fundamentals for the next phase of my career in this AI-native world.
(Full context → now.md)
- Studying Distributed Systems, NLP, ML/AI, Deep-Learning, and AI Application Architectures (Agentic Flows, RAG, etc.).
- Prototyping RAG systems with LangChain + OpenAI/Gemini/Claude.
- Seeking Winter/Spring 2026 internships and Full-time roles (2026)
- Interested in AI Interpretability.
- Owing to my interest in understanding how AI functions 'under-the-hood' and in building responsible AI systems.
(Full journey → career-highlights.md)
- ProdSmiths: Engineering Manager for FinTech infra & legal ops
- AppsForBharat: Led Product Management for Sri Mandir — 5x DAU (Peak of 1M+ DAU, DAU/MAU Ratio of 25%+), Seed → Series A -> Series B
- Hivel: Built fast GenAI MVPs with real use cases
- Yuva Chintana Foundation: Policy and programs for grassroots education
- Qualcomm: Code in billions of devices (PolicyManager, Modem Layer)
(See more → projects.md)
- 🎮 Sri Mandir Gamification: Designed habit loops with spiritual context.
- 📱 PolicyManager @ Qualcomm: Firmware-layer logic on Snapdragon SoCs.
- 🏛 Loan + Legal Infra @ ProdSmiths: Scalable recovery systems for ARCs.
- 🤖 GenAI MVPs @ Hivel: LLMs + Product Data → Meaningful Insights.
(Complete breakdown → technology.md)
Languages: Java, Python, TypeScript, SQL
Infra: Spring Boot, Node.js, Docker, Kubernetes, GCP
AI/ML: LangChain, OpenAI, TensorFlow, Scikit-Learn
Principles: System Design • Prompt Engineering • Product-Led Growth
(Read in full → lessons.md)
- Users > Company > Team > Self
- Technology must serve people.
- Consistency >>> Talent.
- Failure teaches more than Success.
- Trust > Control, Teaching > Managing.
- Good taste is learned from users.
(More details → philosophy.md)
- Systems > Stacks
- Clarity > Complexity
- Respect for time, people, and the codebase.
(Fully detailed → education.md)
- MS in Computer Science, Northeastern University (2024–2026)
Focus: NLP, Distributed Systems, Machine Learning, Deep Learning, AI - B.Tech in Electrical Engineering, IIT Hyderabad (2011–2015) Minor in Computer Science
📍 San Jose, California
📫 [email protected]
🔗 LinkedIn
🧠 Still learning. Still building. Still listening.