Software engineer building high-quality systems at scale, with a track record leading teams and technical initiatives at companies ranging from early-stage startups to mature organizations. My work increasingly sits above the level of a single feature or team: setting technical direction for engineering organizations, establishing the standards other engineers build against, and driving architectural vision for both greenfield and legacy systems.
I specialize in Phoenix/Elixir and Python, with deep experience in distributed systems and, more recently, production AI/LLM infrastructure. At Hatch, I designed a vendor-agnostic abstraction layer across our TTS/STT/LLM pipeline that cut vendor evaluation time and directly enabled new product launches, and built a cross-vendor fallback system that removed single-vendor outages as a failure point for the entire voice pipeline. At papa, I set the LiveView architecture, infrastructure, and coding standards the rest of the engineering org built on, and led the observability effort that consistently surfaced issues before customers reported them.
I look for problems that are still ambiguous where the system needs to be designed. At Hatch, I'm leading the effort to set standards for our legacy monolith, articulating and driving a domain-driven design structure that makes it easier to abstract unique services, test them in isolation, and scale the platform. I bring that same standard-setting instinct to mentorship, advocating for engineering best practices across codebases and experience levels rather than just within my own team.
I'm looking for a role where the technical decisions I make have leverage beyond my own output, where solving the right architectural problem changes how the rest of the org builds, tests, or ships. I'm particularly drawn to teams working at the intersection of distributed systems and applied AI, where the standards I set now shape what's possible later.