MTGIBBS.XYZ

In my current role, I’m responsible for the strategy and delivery of data analytics platforms that support inventory audits and portfolio risk analysis. The work requires balancing speed, accuracy, and trust, and building systems that customers can rely on when making real decisions. I work closely with Product and UX partners to turn loosely defined problems into clear technical direction. A large part of my focus is helping teams navigate trade-offs, establish ownership, and build solutions that are resilient and understandable over time. I care deeply about technical standards and about creating an environment where engineers can move quickly without cutting corners. Lately I’ve been driving our AI-assisted engineering adoption by building the proofs myself: evaluation gates that measure AI-written code in CI, a lab-proven harness that turns a ticket mention into a draft merge request, and the marketplace that distributes our agent tooling. The other half is making the case honestly — briefings, workshops with live demos, and real capacity baselines instead of wishful multipliers. Alongside the platform work, I established and continue to lead DataScan’s engineering internship program in partnership with several local universities, including Georgia Tech, Kennesaw State, and Georgia State. What began as a small effort has grown into a repeatable pipeline for developing early-career engineers — and lately, the first place our AI-native workflows get taught — and it remains one of the most rewarding parts of my role.

In this role, I served as the lead UI engineer, responsible for frontend architecture, tooling, and quality standards across teams. My focus was on consistency and reducing friction, particularly through better CI integration and shared patterns that made the codebase easier to work in and maintain. Equally important was the opportunity to mentor and coach peers. Teaching new frameworks, testing strategies, and engineering practices became a natural part of the job, and it’s where I developed a lasting interest in growing people alongside the software.

Earlier in my career, I led development of a Master Data Management platform intended to consolidate and validate company-wide data. The system emphasized correctness while providing an interface that allowed users to safely understand and update records. This work supported downstream capabilities such as fraud detection and prevention, and it reinforced the importance of data quality, validation, and careful design decisions early in a system’s life.