Senior Software Engineer

At Gigaton, we’re on a mission to cut gigatonnes of carbon emissions from the world’s biggest emitting industries (like cement, steel and glass), by building autonomous AI control and optimisation systems that learn and leverage the physics of manufacturing. Our products run heavy industrial plants more efficiently, more stably, and with lower emissions in real time - laying the foundation for the next industrial revolution. We are a team of scientists, engineers, builders, and operators who love hard problems, have high standards, and want to make change happen in the physical world. We care about deep tech, but we care even more about whether it delivers cost and carbon impact in a live plant, with real people, under real constraints. With Gigaton, you’ll solve really tough problems in places few people ever get close to, and build something that actually helps the planet. Are you up for the challenge? About the role We’re looking for a Senior Software Engineer to join our Platform team and help us build reliable software for a complex, real-world AI product. The Platform team works across a broad range of problems at Gigaton, from CI/CD for our monorepo and networking and data integration with on-premise plant systems, to hardening our IoT OS image and building customer-facing software around our control systems. The work is currently split across two squads: Enablement, focused on helping engineers move faster. Product, focused on supporting our control software. Whichever squad you join, you’ll work across technically challenging problems with plenty of scope to learn, contribute and shape how we build software. Your main responsibilities Write reliable, well-tested software in Python and Terraform. Monitor, support and improve software running in production. Mentor less experienced engineers and help them develop their craft. Identify, articulate and drive architectural improvements. Bring strong software engineering practices to code developed across the wider engineering and ML teams. Contribute to improving the quality, maintainability and reliability of our systems. Bonus experience You don’t need all of these, but experience in any of the following would be useful: Control engineering, machine learning or MLOps. AWS IoT, Greengrass or Mender for managing device fleets. Working across multiple cloud environments, such as AWS, GCP or Azure. Managing CI/CD environments using GitHub Actions. Building production artefacts using tools such as Docker. Functional programming languages such as Haskell, F# or Elm. Building or working with more complex AI-enabled workflows beyond simple prompting. You’ll excel if you are Excited by complex technical domains and enjoy getting to grips with unfamiliar systems. Highly collaborative and comfortable working across software, ML and other disciplines. Familiar with practices such as testing, pairing, mobbing and iterative software development. Pragmatic about engineering trade-offs and know when good en