Professionally, I am a senior software engineer with experience across the entire software development lifecycle in many domains using a wide variety of programming languages and technology stacks.

Personally, I am an extremely curious lifelong learner with a passion for building cool or interesting (and sometimes useful) things. When not busy working on other things, I can usually be found tinkering around with my Emacs config.

I started my career in video game development, particularly on the server side of massively-multiplayer games, for companies such as BioWare, Electronic Arts, Sony Computer Entertainment, and Midway. This phase of my career really cemented my passion for building high-performance, scalable, and secure distributed systems.

Most recently, I worked for Samba TV as a principle software engineer. Samba TV is a technology and data company that specializes in television and cross-platform audience measurement, analytics, and advertising solutions. Its core business revolves around collecting and analyzing viewership data from connected TVs and other devices to help media companies, advertisers, and marketers make data-driven decisions about content performance, audience engagement, and advertising effectiveness.

It was at Samba TV that I really began to see the value of containers. This ultimately led me to blazing the trail for orchestrating these containers at scale with Kubernetes in AWS. While we succeeded in operating our services and other workloads in Kubernetes, the increase in complexity and the baseline knowledge required made the developer experience difficult when getting started. As a developer myself, I could empathize. As a platform engineer I could address the problem.

I prototyped our first internal developer platform, and refined it over three generations to provide a platform offering developers golden paths with guardrails in a self-service, multi-tenant, GitOps-managed Kubernetes cluster fleet running both in AWS and our on-premise datacenter.

I still find platform engineering interesting and challenging, and the emerging AI capabilities have proven to be useful to me in the diagnosis of problems, as well as human-in-the-loop remediation of them.

I have been building and learning with agents such as Claude Code and OpenCode, as well as the latest madels appropriate to my work, typically Anthropic and Open AI models. I have also been developing custom agents with various SDKs in Python and TypeScript. Most recently, I have been building local RAG systems to further enhance results with hybrid lexical and semantic search.