About

I work at the convergence of data infrastructure and AI, as a founding engineer on an agentic data fabric platform for enterprises with complex operational data estates. My scope runs from API contracts and identity models through agent execution, retrieval, evaluation, and Kubernetes delivery, plus the hiring and the standards that keep all of it coherent.

The arc that got me here is unusual on purpose. I started inside the SAP HANA database core, building lockless data structures and chasing nanoseconds with SIMD and RDMA. Then a robotics startup, directing the software that assembled burgers autonomously. Then a big-data platform at SparklineData that Oracle acquired, and Spark-as-a-Service for Fortune 500 workloads at Oracle itself. Then engineering leadership in healthcare: telehealth at eVisit, health-equity fintech at Soda Health. In between, I founded Lakeshore Labs, an AI agents consultancy serving enterprises across Southeast Asia and the Gulf.

Each layer taught a different thing: databases taught precision, robots taught humility about the physical world, platforms taught leverage, healthcare taught what regulation does to architecture, and founding taught what any of it is worth to a customer.

What I care about now is making agentic systems trustworthy enough for production: drawing clean lines between data and AI infrastructure, and growing the engineers who own those layers into people who raise the bar themselves.

Earlier still: B.S. in Electrical Engineering and Computer Science at UC Berkeley, summa cum laude, Haas Scholar. I have taught blockchain engineering in Vietnam, researched nanowires, and managed an Engineers Without Borders project. I would rather build the platform than the demo.