ABOUT
I'm a software engineer with 6+ years of experience building distributed systems, data infrastructure, and large-scale software platforms. I design high-throughput systems that ingest, process, model, and serve data for product features, operational analytics, and AI-powered applications.
I like work that connects engineering execution to measurable outcomes: stronger reliability, lower infrastructure cost, higher platform adoption, faster product delivery, and clearer business impact. Most of my technical work sits across distributed processing, data modeling, pipeline platformization, and observability.
I use AI-assisted development tools daily, including Claude Code and OpenAI Codex. I see them as part of a production engineering workflow: faster iteration, strong test harnesses, clear review loops, and continuous verification from prototype through production.
I graduated from Macalester College with majors in Computer Science, Mathematics,
and Philosophy. My senior thesis explored how theoretical research, especially algebraic and topological methods, can generate new approaches to AI and high-dimensional data analysis. That background shapes how I approach software systems where code, data, models, and production behavior increasingly overlap.