// about me

I build mission-critical infrastructure for the most ambitious engineering problems I can find. My dad ran a technology solutions business, and growing up I watched him wear every hat imaginable. Seeing what was possible when you built your own tools stuck with me—I've been chasing that autonomy and scale ever since.

I studied Computer Science at the University of Florida, minoring in Electrical Engineering. Outside the classroom, I chased applied AI—deploying neural networks for COVID-19 detection in retail environments and leveraging AlphaFold2 for cancer protein structure prediction. By graduation, I knew exactly the kind of technical velocity I wanted.

I started at Amazon as a software engineer on Alexa AI, building model deployment pipelines at global scale. When large language models fundamentally shifted the industry, I moved to Amazon AGI. I helped build the infrastructure that powered the Amazon Nova model family, touching everything from multi-modal inference to pre-training data pipelines.

Most recently, I joined Amazon Leo (formerly Project Kuiper) as the founding software engineer for the Launch Operations team. I designed and built the software that tracks and verifies satellite health from the factory floor to the launch pad. It's a high-stakes, zero-tolerance environment built to scale for an eventual 7,736-satellite constellation. What started as just my manager and I quickly scaled into an eight-person engineering org within a single year.

My technical domain has constantly shifted—from consumer voice AI, to foundational LLM training, to orbital launch logistics. But the core motivation remains the same: I want to build systems that matter, alongside people who actually care about the craft.

Outside of my IDE, I'm a car enthusiast with a heavy bias toward American muscle. I drive a manual Dodge Challenger Hellcat and an H2 Hummer—both yellow, matching the site you're reading right now. I cycle, run, and spend most of my downtime with my rescue dog, Rocky.