About
I started my career in a room where national budget numbers were not abstractions. At the Prime Minister's Office of India, I led a 15-person team building analytics systems that tracked over $360 billion in government expenditure. Cabinet Ministers used our dashboards to make allocation decisions. The work taught me that data only matters when it changes a decision, and that the hardest product problems are not technical. They are about trust.
From there, I moved toward systems that operate in the physical world. At Attentive.ai and Amazon, I worked on computer vision and robotics for geospatial analysis and fulfillment operations. At PlanetIQ, I turned satellite radio occultation data into weather products used by forecasters and climate researchers. Each role reinforced the same lesson: AI products in physical environments cannot afford the iterative sloppiness that software-only products tolerate. When a robotic arm drops a package or a weather model misses a storm, the cost is not a bad review. It is concrete.
Today, I am completing my MBA at Kellogg School of Management (Northwestern, class of 2026) and building AI operations systems at Clear Skies Hydrogen, a hydrogen infrastructure company based in San Francisco. I am designing multi-agent AI systems for infrastructure that barely exists yet, which means the training data I need does not exist either. It is the most interesting product problem I have worked on.
Beyond the work
I read Soviet war novels for their treatment of moral complexity under pressure. Vasily Grossman's writing on individual conscience within vast systems has shaped how I think about building technology responsibly. I study Neo-Confucian philosophy, particularly Wang Yangming's unity of knowledge and action. His central claim, that knowing and doing are inseparable, is the closest thing I have to a professional philosophy. I believe the best product thinkers are those with wide peripheral vision: history, philosophy, and physical sciences inform how I reason about technology more than most business frameworks do.
What I am looking for
Exploring AI product roles at frontier companies where I can bring physical-world deployment experience to the next generation of AI products. I want to work where the models meet the constraints, where latency is measured in milliseconds and mistakes have consequences you can point to.