I like systems that stop being interesting.
The best compliment I've had on a platform is that people stopped thinking about it. It just worked, and they got to spend their attention on their own problems instead of mine.
I'm a software and platform engineer based in Canton, GA. I started in DevOps automation, moved into full-stack and backend engineering, and spent the last two years leading a security platform used across thousands of enterprise applications.
How I got here
I started as a DevOps co-op at Georgia Tech Research Institute, automating VM provisioning and Kubernetes cluster checks. That job teaches you fast that most outages are a process problem before they're a technical one, and that anything done by hand twice should probably be a script.
From there I moved into full-stack software engineering — first at Techquidation, then at Endava building financial-services web applications and SDK integrations. That's where the automation habit turned into building the actual product instead of just the pipeline around it.
At AT&T I led the Sensitive Data Discovery platform: onboarding, scanning, remediation, and compliance workflows for thousands of enterprise applications. Automating what had been manual work let the team shrink from 57 to 28 people while scanning throughput went up 2.22x and annual operating cost dropped from $8.3M to $3.5M.
These days I'm building RAG and agent tooling on the side, and treating AI systems the same way I treat any other production dependency: useful where it earns its place, with a contract and a fallback everywhere else.