I build software that does real work.

For 19 years I've turned messy operational problems like support, data migration, QA, and customer enablement into products that scale. Lately that means applied AI for the parts of enterprise software people usually avoid.

I'm the Director of Data Services and AI Solutions Architect at Mirabel Technologies, where I built and lead the database-services function from the ground up: a team of five running an 800+ database production environment for a multi-tenant SaaS platform.

A lot of the role is consultative. I meet directly with publishers to understand their pain points, then design and build custom solutions for them: bespoke reports, tailored workflows, and integrations with third-party systems. I also help shape where the platform goes next, partnering with executive leadership on its technical direction and roadmap.

My recent work makes institutional knowledge usable at scale: a self-service API platform with a visual workflow builder, an AI-assisted regression-testing suite with DB-level assertions and self-healing tests, a retrieval-augmented knowledge assistant that curates support history into trustworthy cited answers, and a Jira deep-dive system that turns tickets into engineering analysis and guarded draft pull requests. A few are written up in my work →

I also build NectarStudio, where I ship AI products end to end, from the database and API to the workflow engine and UI.

I'm at my best where the problem isn't neatly contained: legacy databases, enterprise CRM workflows, support operations, and AI that has to survive real users and real data. I care about systems that are accountable, sourced, evaluated, and safe to trust. I was an early adopter of AI development tooling (Claude, Cursor) and lean on it to ship faster without lowering the bar.

Off the clock, I'm a husband and girl-dad of two: one studying aerospace engineering at Purdue, the other an aspiring artist. I build remotely from Indiana, by way of Miami, Nashville, and Huntington Beach.