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Gigaton is building autonomous AI control and optimization systems for heavy industrial manufacturing (cement, steel, glass) to cut gigatonnes of carbon emissions. The company develops software and hardware that runs industrial plants more efficiently, stably, and with lower emissions in real time.
You'll join the Platform team as a Senior Software Engineer, working across two squads: Enablement (helping engineers move faster) and Product (supporting control software). The Platform team handles CI/CD for the monorepo, networking and data integration with on-premise plant systems, hardening the IoT OS image, and building customer-facing software around control systems.
Key responsibilities:
- Write reliable, well-tested software in Python and Terraform
- Monitor, support and improve production software
- Mentor less experienced engineers and help develop their craft
- Identify, articulate and drive architectural improvements
- Bring strong software engineering practices across the wider engineering and ML teams
- Contribute to improving quality, maintainability and reliability of systems
You'll work on technically challenging problems with scope to learn, contribute and shape how Gigaton builds software. The role involves collaboration across software, ML and other disciplines, working with ambiguity and evolving requirements, and taking ownership of problems through to production.
Gigaton values concrete honesty, autonomous ownership, high standards, and pragmatism about engineering trade-offs. The team includes scientists, engineers, builders and operators focused on delivering real cost and carbon impact in live plants under real constraints.
BENEFITS: Equity (share options), flexible working, 30 days holiday plus bank holidays, generous pension scheme.
REQUIREMENTS:
Must-have: Strong software engineering fundamentals; experience writing production Python and/or Terraform; comfort with testing, iterative development and collaborative practices; ability to work across complex technical domains and unfamiliar systems; pragmatism about engineering trade-offs.
Bonus experience (not required): Control engineering, machine learning or MLOps; AWS IoT, Greengrass or Mender; multi-cloud environments (AWS, GCP, Azure); GitHub Actions CI/CD; Docker; functional programming languages (Haskell, F#, Elm); AI-enabled workflows beyond simple prompting.
