AI Infrastructure · Systems · Security
Visionary, tactical, and collaborative software engineer. Passionate about designing efficient, secure, and scalable systems; building; and delivering a measurable impact.
Now
I partner with technical leaders and engineering teams at leading AI companies to architect, build, and harden what they run on Modal.
I root-cause the failures that only surface under real production load, and ship the fixes deep in the platform runtime, so launches hold.
I lead technical scoping for platform migrations, redesigning how workloads are structured so teams can keep growing without re-platforming.
I built a reusable analysis that turns raw utilization data into recovered spend, and it is becoming a product surface rather than a one-off.
I turn fleet-wide telemetry into pricing, SLA, and roadmap decisions, and work with product teams to put the metrics that matter in front of customers.
I benchmark model inference so teams choose their hardware, runtime, and serving shape on evidence instead of guesswork.
I map platform semantics end to end so the documented path is also the correct one.
Previously: Azure core HPC and AI training platform at Microsoft; usable privacy and security research at CMU CyLab (publications). Computer Science grad from Carnegie Mellon University.
Selected projects
Research