AI becomes a systems problem the moment it meets infrastructure.

I build AI systems for distributed infrastructure: guarded LLM workflows, telemetry-driven data movement, and reproducible systems evaluation. My approach comes from both research and production backend engineering, so I treat constraints, failure modes, and operational evidence as part of the design—not as cleanup after a model works.

I am a Computer Science PhD student and Kummer Doctoral Fellow at Missouri S&T, following three years of backend engineering at Kona Software Lab. I am interested in research roles where AI, distributed systems, networking, and careful software engineering meet.