This is a platform engineering role on a team that keeps the software behind an industrial AI product running smoothly. The work is mostly Python and Terraform, covering build pipelines, connections to plant systems, device software and customer-facing tools. A strong candidate writes well-tested code, supports live systems, mentors others and is happy improving existing systems as well as building new ones.
How it fits the AI era
The product itself is AI that controls heavy industrial plants, so this role sits underneath it, making sure models and control software ship and run reliably. Better tooling and sound engineering habits help ML colleagues move faster and with fewer surprises. Judgement about trade-offs, ownership of production problems and clear teamwork across disciplines stay firmly human.
How it builds AI experience
Someone in this role would see how an AI control system is deployed, monitored and supported in real plants, which is a rare view of AI beyond the lab. Working beside ML engineers on shared code quality and release practices builds practical MLOps understanding. Anyone preparing can explore device fleet management, CI/CD and AI workflows that go beyond simple prompting.
Worth showing
- Production Python with strong tests
- Terraform and cloud infrastructure
- Owning systems in production
- Mentoring other engineers
This is our own read, written from the employer’s posting and the company’s Spotlight. The employer’s posting is the source of truth for the role.
About Gigaton
Industrial artificial intelligence platform providing self learning process control to cut fuel costs and carbon emissions in energy intensive manufacturing.
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