Solutions Engineer

Our Mission 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 applying cutting‑edge AI where it matters most. We’re a small and growing team of scientists, engineers, and strategic thinkers who care deeply about impact and believe in getting there with good humour and urgency. Our SaaS products help heavy industry optimise operations in real time, cutting costs and carbon today while building the foundation for the next industrial revolution.

Our Mission

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 applying cutting‑edge AI where it matters most.

We’re a small and growing team of scientists, engineers, and strategic thinkers who care deeply about impact and believe in getting there with good humour and urgency. Our SaaS products help heavy industry optimise operations in real time, cutting costs and carbon today while building the foundation for the next industrial revolution.

About the Role

We’re seeking a Solutions Engineer – Process Control to join our Product and Solutions Engineering team and sit on the frontline of industry decarbonisation.

This role blends industrial process expertise, control engineering, and deployment leadership . You’ll work directly with process engineers and plant operators to understand complex chemical processes, design optimal AI control strategies, and integrate Gigaton’s AI into live production environments, ensuring our technology aligns with operational realities and delivers measurable value.

Think of it as the process engineer’s trusted partner — technical, pragmatic, and collaborative. You’ll lead deployments, translate AI outputs into actionable control strategies, and help shape Gigaton’s approach to scaling advanced process optimisation across global industrial sites.

Your Main Responsibilities

• Deploy & integrate Gigaton AI into live cement and industrial plants, ensuring stable, safe, and effective operation within existing process control frameworks.
• Collaborate with plant and process teams to identify optimisation opportunities, tune control loops, and validate performance improvements.
• Analyse plant data to identify opportunities and evaluate the performance of Gigaton’s software.
• Develop and refine control strategies , leveraging APC, MPC, and PID principles to bridge AI recommendations with practical plant control systems.
• Build trust and engagement with process engineers and operators by clearly explaining technical decisions and demonstrating measurable benefits.
• Collaborate with machine learning engineers to refine algorithms and recommendations based on real‑world outcomes.
• Support deployment playbooks and templates, ensuring repeatable, scalable, and high‑quality rollouts across plants.
• Act as a feedback link to Gigaton’s product and machine learning teams, providing field insights that shape our product roadmap and model development.
• Travel to sites (~1 week/month) to work hands‑on with teams during commissioning, testing, and optimisation phases.

What a Great Fit Looks Like

• Strong background in process or control engineering , ideally in cement, chemicals, energy, or heavy manufacturing.
• Experience with advanced process control (APC/MPC/PID) systems and process optimisation projects.
• Familiarity with industrial automation systems (e.g., DCS, PLC, OPC, historian systems).
• Understanding of AI/ML applications in process control (forecasting, optimisation, anomaly detection) is a plus.
• Comfortable collaborating with operators, engineers, and data scientists — bridging industrial know‑how with data‑driven insights.
• Analytical and hands‑on mindset: capable of diagnosing process instabilities and proposing actionable solutions.
• Excellent communication skills — able to build credibility and trust in complex industrial environments.
• Willingness to travel regularly to deployment sites (~25%).

You’ll Excel If

• You’re a practical problem‑solver who enjoys working on real‑world process challenges.
• You’ve implemented or tuned control systems and understand how to balance process stability, quality, and energy efficiency.
• You’re confident working across technical, operational, and business interfaces , turning complex problems into structured solutions.
• You thrive in dynamic, high‑impact environments , where every deployment directly contributes to decarbonisation.
• You can translate between AI outputs and process logic , ensuring plant teams understand and trust automation strategies.

Success in This Role Means

• Plants achieve measurable performance improvements — lower costs, reduced CO₂, improved stability.
• Customer process engineers trust you as a reliable partner who understands their world.
• Deployments become more repeatable, efficient, and scalable thanks to your control and process insights.
• Gigaton’s solutions evolve from AI algorithms into robust, operator‑friendly process control systems.

You are not expected to check every box, and we’d love to hear from you even if your experience isn’t an exact match.

The interview process

1. Learn about us during a screening with our talent partner
2. If this item goes well, we will submit your profile to the hiring lead. You will get feedback either way
3. Technical Interview
4. Cement Process Optimisation
5. For candidates: Work through a kiln optimisation scenario, balancing process stability, clinker quality, fuel use, and emissions to recommend an operating strategy.
6. What it’s assessing: Ability to reason about complex plant dynamics, weigh competing trade‑offs, and connect process decisions to overall plant performance and cost impact.
7. Technical Interview 2:
8. Interview 2: Control Systems
9. For candidates: Discuss and design control strategies for a high‑temperature process (e.g. cement kiln), using a mix of classical control (e.g. PID, cascade, feed‑forward) and advanced methods (e.g. MPC, optimisation, AI‑assisted control). Explain how you would structure the control problem, choose manipulated/controlled variables, handle constraints and delays, and tune or validate your approach with real plant data.
10. What it’s assessing: Depth in control theory and practical control design; ability to reason about closed‑loop behaviour, robustness, and safety; understanding of how advanced control and data‑driven methods can improve stability, efficiency, and emissions in real industrial environments.
11. Operating Principles Interview
12. Meeting with our CEO

We believe hiring is a two‑way process. Just as we’ll reference‑check candidates before making a final offer, we encourage you to reference‑check us by chatting with team members you haven’t yet met. Ask anything. We’ll answer with Concrete Honestly.

Once interviews are done, we’ll move quickly to a decision, and we’re always happy to give feedback at any stage.

In return for your hard work, we’ll give you

Equity in the company: When we win, you win. You’ll get share options, so you’re part of our journey from the inside.

Flexible working: We trust you to know how and when you work best and to work that out with your team.

30 days of holiday (plus bank holidays). Rest is productive. Take the time you need to recharge

A generous pension scheme. We’re planning for the future in more ways than one.

Our Operating Principles

Go Gig or Go Home: High Bar, All In. What we do matters to humanity, to our customers and to each other. We hold ourselves to an extraordinarily high bar and bring the urgency this mission requires.

Concrete Honesty: Be honest. As concrete forms the foundation of our world, genuine honesty and transparency are the bedrock of our culture.

Autonomous Ownership: High agency, high ownership. We build systems that take control and make things better. We do the same: see it, own it, drive it.

Cement it with Kindness & Fun: Have fun, be kind. We're here to extend Earth's life, but ours is still limited. We want to enjoy the ride. To see these in full, go to Gigaton’s Operating Principles Notion page.

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