I write software for systems where being wrong is expensive: vision pipelines running on a moving production line, platform infrastructure at a $247B pension fund, services that have to stay up while traffic triples.
Most of what I'm good at is diagnostic. Working out which layer a failure actually lives in (application, container, network, or the camera itself) is usually harder than the fix, and I've gotten fast at it. The rest of the job is building the tooling so the same problem doesn't need a person the next time it shows up.
Right now that's machine vision at Tesla. Before that, distributed platform work at Ontario Teachers' Pension Plan and a few years of shipping things real users depended on. Outside of that I founded McMaster's self-driving car club, where we're building a ROS perception stack from the ground up.