Head of Engineering

Posted 5 Days Ago
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London, Greater London, England, GBR
Hybrid
Entry level
Artificial Intelligence • Software • Industrial • Automation
The Role
Lead and scale a high-performing software engineering organization building real-time AI control and optimization systems for heavy industrial plants. Responsibilities include coaching engineers and engineering managers, strengthening software quality and delivery practices, aligning engineering plans with company priorities, supporting machine learning and research teams, making technical trade-offs, and developing future technical leaders. The role requires continued technical involvement in architecture, debugging, design reviews, and pairing within a complex, safety-critical environment.
Summary Generated by Built In

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 Head of Engineering to join our team and help us build AI that controls the world's most complex industrial plants in real time.

What will this role achieve?

The goal: Build a high-performing software engineering organisation that reliably delivers customer value while providing the platform and infrastructure that enables our machine learning and research teams to succeed.

Outcome – an elite engineering team. We've built solid foundations: continuous deployment, modern observability, high test coverage and a fear-free culture. You'll help the organisation continually improve by coaching engineers and team leads, strengthening engineering practices, and creating space for the technical investments that keep us moving quickly.

Outcome – a culture of quality. We operate in a complex, safety-critical domain while moving quickly. Software quality is how we resolve that tension. You'll embed planning, review and engineering practices that help teams identify risks early, ship confidently and learn continuously.

Outcome - shared alignment. We have ambitious objectives, and a high bar for performance. We need make measurable progress through tangible, realistic goals. You'll partner with the Head of Machine Learning, Head of Product, and the CTO to turn company priorities into realistic engineering plans. You'll help teams make thoughtful trade-offs, maintain focus, and deliver predictably as priorities evolve.

Outcome - the next generation of technical leaders. As Gigaton grows, our success depends on developing leaders at every level. You’ll coach team leads to become confident technical and people leaders, establish clear expectations and management frameworks, and create an environment where leadership is nurtured deliberately.

What a great fit looks like
  • You have a strong software engineering background and have successfully transitioned into engineering leadership.

  • You have experience leading through team leads or engineering managers, and enjoy developing other leaders.

  • You understand how to introduce enough structure to help team scale, without introducing unnecessary process.

  • You remain technically proficient and enjoy working directly with engineers on architecture, debugging, design reviews, or pairing.

  • You understand modern software engineering practices, including TDD, pair programming, and continuous deployment.

You’ll excel if
  • You are passionate about climate impact and excited about Gigaton’s mission to decarbonise heavy industry.

  • You enjoy working with domain experts to solve complex real-world problems.

  • You have an educational background in the physical sciences.

  • You have experience building software for scientific, industrial, or data intensive systems.

  • You have worked closely with machine learning or data engineering teams.

💡 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.

We’re building a team that reflects the world we want to change. Our people come from all walks of life - different countries, cultures and experiences - and we think that’s one of our biggest strengths. We’re committed to creating a workplace where everyone feels safe, respected and celebrated. No matter your background, if you’re excited by what we do, we want to hear from you.

The interview process

Our interview process is designed to understand how you think, lead, and work with others. We are not looking for a perfect match against every requirement. We are looking for evidence that you can build a high-performing engineering organisation in a complex, high-stakes domain.

The process has four main stages.

  • Pair programming

You’ll work with one of our engineers on a small technical exercise. We are not assessing memorised syntax or speed under pressure. We are interested in how you reason, how you collaborate, how you use tests to guide your work, how you learn from documentation or tools, and how you communicate while solving an unfamiliar problem.

  • System design

You’ll walk us through a real system you have worked on and had meaningful architectural influence over. We’ll ask you to describe the problem, the constraints, the operational characteristics, the design choices you made, and how the system evolved over time.

  • Management scenarios

You’ll work through a set of realistic management scenarios: production incidents, conflicting priorities, delivery pressure, and career development.

There are no single correct answers. We are looking for how you diagnose situations, how you create alignment, and how you help teams learn. This stage is intended to understand your management style, your operating principles, and your ability to lead through complexity.

  • Operating Principles

We’ll discuss examples from your past work that relate to how we operate: ownership, ambition, honesty, adaptability, and kindness. We’re proud of our operating principles and they are published on the internet.

Finally, 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 to team members you haven’t yet met. Ask anything. We’ll answer with Concrete Honesty.

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.

Skills Required

  • Strong software engineering background with successful progression into engineering leadership
  • Experience leading through team leads or engineering managers
  • Experience developing and coaching other leaders
  • Ability to introduce scalable structure without unnecessary process
  • Technical proficiency and willingness to work directly with engineers on architecture, debugging, design reviews, or pairing
  • Understanding of modern software engineering practices, including TDD, pair programming, and continuous deployment
  • Passion for climate impact and decarbonizing heavy industry
  • Enjoyment of working with domain experts on complex real-world problems
  • Educational background in the physical sciences
  • Experience building software for scientific, industrial, or data-intensive systems
  • Experience working closely with machine learning or data engineering teams
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The Company
33 Employees
Year Founded: 2020

What We Do

Gigaton develops autonomous AI control and optimization systems for heavy industrial plants, beginning with major emitting sectors such as cement, steel and glass. Its software learns from manufacturing physics to operate plants more efficiently and stably in real time, lowering operating costs and carbon emissions. The company combines deep technology with practical industrial deployment to accelerate decarbonization across energy-intensive manufacturing.

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