About

Deep backend at scale. Now bringing AI into it.

Full-stack, silicon up

From ESP32 sensor telemetry to Blazor front ends and distributed .NET services — I work across the whole stack, plus infra and architecture.

Performance at scale

~20k requests/second, sub-10ms hot paths, and a 1.8M-user repository served in under a minute.

Reliability first

Led an access-service rebuild delivered on time, serving in production with zero major bugs reported. Correctness under load.

Agentic AI in production

Building multi-agent systems on watsonx and Azure — with human-in-the-loop governance in regulated domains.

I'm a senior full-stack engineer with 9+ years building reliable, high-performance systems in .NET and .NET Core — distributed systems, microservices, and the kind of data-heavy services that have to stay fast under real load.

My work has centered on systems where correctness and latency matter: a licensing platform fielding roughly 20k requests per second, a service that materialises a 1.8M-user, ~6GB repository in under a minute with sub-10ms average response on hot paths, and 20+ systems delivered and maintained. I led an access-service rebuild — delivered on time, serving in production with zero major bugs reported — and I mentor the engineers around me.

Now I'm pointing that systems background at AI. At AIM I build agentic-AI products end to end: a multi-agent compliance orchestrator on IBM watsonx Orchestrate and Azure, and an agentic platform for maternal and chronic care with human-in-the-loop clinical oversight. The goal isn't AI for its own sake — it's bringing agentic capabilities into systems that already have to be reliable.

There's an embedded thread running underneath all of this. I'm an IoT hobbyist — ESP32, Arduino, MicroPython — which means I tend to understand systems from the silicon up. That perspective, from sensor telemetry to distributed services, is where I do my best work.