A path that wasn't straight — but always pointed at the same thing.

I tested industrial automation machines — CNC lathes, switchgears — adjusting drives mechanically and working close to the hardware. But it was the programming side, writing C and C++ and working with logic gates, that pulled me toward quality: I cared less about building a thing than about whether it actually worked, reliably, every time.

Three years testing Sharp's document-solutions products across three platforms — a cloud web portal, Windows desktop, and mobile — and the work that made testing click for me. It's where I built my foundation: structured manual testing on real enterprise products, and my first professional automation — expanding and maintaining Selenium suites inside a mature framework, guided by senior QA engineers. Working across the full spread of platforms instead of just one is what I loved, and it taught me what disciplined testing actually looks like.

As the team moved into in-house development, I expanded and maintained the automation framework across web and mobile — adding Appium and REST Assured coverage, contributing reusable test utilities, and supporting the Jenkins CI pipeline — while working QA across the UI, API, and data layers and turning designs into testable requirements alongside designers and developers.

A Master's with a machine-learning emphasis, where I learned to build data pipelines and run inference across structured and unstructured datasets — and got a grounding in data ethics: how data is sourced, used, and governed. It shaped how I work day to day, including how deliberately I use AI in my development practice — orchestrating the design and direction myself, and keeping what I build transparent rather than a black box I can't explain.