Solutions 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 seeking a Solutions Engineer to join our Solutions Engineering team and sit on the frontline of industrial decarbonisation.

This role blends industrial process expertise, control engineering, and deployment leadership. You’ll work directly with plant management, process engineers and operators to understand complex chemical processes, design optimal AI control strategies, and integrate Gigaton’s AI into live production environments. Your mission is to ensure that we delight our customers by using our AI solutions to solve critical operational problems and deliver real, measurable cost and carbon impact.

Your Main Responsibilities

• Build trust and engagement with plant managers, process engineers and operators by clearly explaining technical decisions and demonstrating measurable benefits aligned to operational needs.

• Analyse plant data to assess and identify opportunities, and evaluate the performance of Gigaton’s software.

• Develop and refine control strategies, leveraging APC, MPC, and PID principles.

• Deploy and integrate Gigaton AI into live plants, ensuring stable, safe, and effective operation.

• Collaborate with plant and process teams to identify optimisation opportunities, tune control loops, and validate performance improvements.

• Collaborate with machine learning engineers to refine algorithms and recommendations based on real-world outcomes.

• Create and refine deployment playbooks and templates, ensuring repeatable, scalable, and high-quality rollouts across plants.