I lead teams building AI applications in TypeScript, Python, and Go. My work includes agentic AI tools for the test and evaluation community and evaluation benchmarks for retrieval performance, adversarial prompting, and agent behavior.
I inherited a system of 26 microservices across 89 repositories and overhauled its DevSecOps and CI/CD workflows: SAST/DAST, SBOM generation, builds, and testing. I built a Kubernetes cluster from the lab’s high-performance desktops and parallelized end-to-end simulations, reducing test runs from seven days to four hours. My work also includes ML evaluation workflows and a deployment dashboard supporting approximately 20 developers. I stay hands-on with Python, Go, Java, and service integration while mentoring engineers and guiding architecture.
On my workbench: PicoScope MCP, Ryobi moisture-meter decoding, and acoustic monitoring for a coffee roaster. These projects connect software with real signals and physical equipment. Each repository documents its scope and limitations.
At PeopleTec, I established DevOps practices for several projects. I now lead the team and define delivery requirements and engineering standards, while team members handle most day-to-day DevOps implementation.
I architected and built a full Go application, led its development team as technical lead, and subsequently handed off team leadership.
I am pursuing a PhD at Auburn University, researching ice detection with flexible capacitive sensors and relaxation oscillators. My earlier research included in-situ temperature and moisture monitoring in hay bales to identify conditions associated with spontaneous-combustion risk; I was first author of the 2018 conference paper on that device.