I build things with cloud infrastructure and AI.
I've spent 12 years in telecom and cloud infrastructure at Nokia and Verizon, mostly making sure large-scale platforms stay up and building automation so people don't repeat work. These days I'm deep in AI/ML infrastructure: local LLM inference, agentic workflows, and figuring out how to make AI tools that actually work in production.
I like hard problems, ugly debugging sessions, and shipping things that other people use.
An AI coding agent that plans, writes, and reviews its own code.
Three-phase pipeline: a planner breaks down the task, a coder executes edits with tool calls, and a reviewer validates the output. Runs local LLMs on consumer GPU hardware (AMD RX 7900 XT with ROCm). I built it because I wanted a coding assistant I could actually trust with my codebase.
Patent intelligence for people who don't want to read 40-page claims.
Full-stack web app that uses Vertex AI to analyze patent claims and flag potential NPE (patent troll) activity. Built with Next.js, Postgres, and a curated watchlist of 130+ known entities. The kind of project where I learned that legal data is messier than telecom data, which is saying something.
B.S. Computer Engineering from Texas A&M ('13). Started at Nokia doing telecom platform integration and customer-facing upgrades. Moved to Verizon's cloud platform team where I've spent the last 8 years working on OpenStack, OpenShift, and the automation that holds it all together. AWS Certified Cloud Practitioner. I write Python, Bash, and whatever else the problem needs.