About Gigaton
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.
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.
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.
Requirements
•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.
•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 enough now is better than perfect later.
•Comfortable working with ambiguity and evolving requirements.
•Able to improve existing systems, not just build new ones from scratch.
•Happy to take ownership of problems and follow them through into production.
You are not expected to check every box, and the company would love to hear from you even if your experience isn't an exact match.
Interview process
1.Talent Partner conversation — a conversation about your background, what you're looking for and what interests you about Gigaton, plus more context on the role, the team and the interview process.
2.Hiring Manager interview — a deeper conversation about your experience and some of the technical problems you've worked on, exploring work you've owned, decisions you've made, how you approach engineering trade-offs, and fit on both sides.
3a. Pair Programming - remote session — working with one of the engineers on a small technical exercise using Python and Terraform, assessing reasoning, collaboration, use of tests, learning from documentation/tools, and communication.
3b. Technical Onsite — takes place in the London office, one session: System design — walking through a real system you've worked on and had meaningful influence over, discussing the problem, constraints, operational characteristics, design decisions, trade-offs and how the system evolved.
4.Operating Principles interview — exploring specific examples of how you've demonstrated the company's Operating Principles (Concrete Honesty, Autonomous Ownership, Go Gig or Go Home, Cement It with Fun and Kindness).
5.CEO conversation — with Josh, the CEO, to talk more broadly about Gigaton, its mission, where the company is heading, and whether this feels like the right move for both sides.
Gigaton conducts reference checks before making a final offer, and encourages candidates to reference-check the company too, by speaking with team members they haven't yet met.
Benefits
•📈 Equity in the company: share options, so you're part of the company's journey from the inside.
•🕰️ Flexible working: you work out how and when you work best with your team.
•🌴 30 days of holiday (plus bank holidays).
•🪙 A generous pension scheme.
