---
title: 'Solutions Engineer at Gigaton'
canonical: 'https://feeny.ai/job/solutions-engineer-gigaton-london-5wzqmm9aach0'
type: 'job'
last_seen: '2026-09-11'
---

# Solutions Engineer at Gigaton

- **Company:** Gigaton
- **Location:** London, United Kingdom
- **Compensation:** £60k–£85k
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-03-20
- **Last confirmed live:** 2026-09-11
- **Apply:** https://jobs.ashbyhq.com/gigaton/85907722-9baa-452d-8958-7f18de63667e

## Job description

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 & 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.
- Act as a feedback loop into Gigaton’s product and machine learning teams, providing field insights that shape our product roadmap.
- 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 process or control engineering background, ideally in cement, chemicals, energy or heavy manufacturing.
- Comfortable collaborating with operators, plant managers, engineers, and data scientists, bridging industrial know-how with data-driven insights.
- Strong analytical skills and outcome oriented mindset, able to dig into industrial data, identify root causes, generate actionable solutions, and deliver them.
- Excellent communication skills, able to build credibility and trust in complex industrial environments.
- Excellent project management, working independently to drive clear actions for yourself, your team and the customer, delivering against the plan and managing risks across the project.
- Practical problem-solver who enjoys working on real-world process challenges.
- Willingness to travel: regularly to deployment sites (~25%).

You’ll Excel If

- You thrive in dynamic, high impact environments, fast-paced, ambiguous settings excite you, and where every deployment directly contributes to decarbonisation.
- You take ownership, you thrive when you’re given full responsibility for projects and see them through end-to-end. You spot problems and act decisively to solve them.
- You have experience with industrial control (APC/MPC/PID), automation (DCS, PLC) or data (OPC, Historian, LIMS) systems.
- You have an understanding of AI/ML applications, such as forecasting, optimisation, anomaly detection.
- You have implemented or tuned control systems and understand how to balance process stability, quality, and energy efficiency.
- You are confident working across technical, operational, and business interfaces, turning complex problems into structured solutions and can communicate complex ideas to multiple audiences.

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

- Talent Partner Screen Call: Meet our talent partner and learn more about Gigaton and the role.
- Hiring Manager Screen: Meet one of our Solutions Engineers and discuss if this role is a good fit for you.
- Technical Interviews:
- Cement Process Optimisation
- The Task: Work through a kiln optimisation scenario, balancing process stability, clinker quality, fuel use, and emissions to recommend an operating and control strategy.
- 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.
- Delivery Management
- The Task: Talk through real examples from your career of owning complex industrial software projects end‑to‑end, plus problem solving examples and experience working with software teams. You'll then apply that experience to a live Gigaton scenario.
- What it's assessing: End‑to‑end delivery and accountability, stakeholder management and communication. Ability to problem‑solve individually and with a team in real industrial and customer environments; ability to work effectively with software engineering teams, as well as speed of learning in new domains.
- Operating Principles Interview: Understand how we work and whether Gigaton and you are a good fit for each other.
- Meet with the CEO: Every new potential hire meets Josh

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 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](https://gigaton-technologies.notion.site/gigaton-s-operating-principles) Notion page.

## About Gigaton

## Company Overview
- **One-liner**: Gigaton builds self-learning AI control systems for energy-intensive heavy industries to reduce costs, complexity, and carbon emissions.
- **Entity Type**: Private (Series A, raised $10.4M in October 2025)
- **Headquarters**: London, United Kingdom (primary location; also listed as Canada on LinkedIn)
- **Founded**: 2020
- **Founders**: Buffy Price (Co-Founder), Dr. Noah Miller (Co-Founder & Chief Solutions Officer), Dr. Daniel Summerbell (co-founder role not explicitly stated but listed as Chief Solutions Officer & Co-founder)

## Core Business
- **Primary industry**: Industrial AI / Climate Tech – focusing on cement, steel, glass, and other energy-intensive manufacturing.
- **Target customers**: B2B – heavy industrial plants (e.g., cement manufacturers like Heidelberg Materials), plant operators, and energy-intensive production facilities.
- **Mission**: “To reduce industrial carbon emissions by gigatonnes” – building the self-learning control system for autonomous plants and industrial decarbonization.

## Products & Services
- **Gigaton Self-Learning Control System**: An AI-powered control platform that autonomously optimises plant operations. It is predictive (forecasts process variables), adaptive (continuously retrains models to prevent drift), flexible (switches between cost and production priorities), and explainable (visualises reasons for decisions). Connects directly to the plant’s DCS. Deployable in 8 weeks, delivering 2%+ reduction in fuel-derived carbon emissions and significant cost savings. Proven at Heidelberg Materials with a 4% reduction in fuel cost index and 33% reduction in C3S variability.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed.
- **Key Metric**: Total funding of **$17.1M** (USD) across 6 rounds, including a $10.4M Series A (October 2025), $4.8M Seed (led by Planet A Ventures, 2022), and earlier grants.
- **Notable Investors/Partners**: 2150 VC, Clean Growth Fund, Plural, Planet A Ventures (lead seed), and board chair Mike Laven.
- **Growth Signals**: Headcount grew 41.7% year-over-year (29 employees as of mid-2026). Monthly growth rate of 9.7%. Key customer win: Heidelberg Materials deployment. Active hiring with 6 open positions (Machine Learning Engineer, Product Manager, Solutions Engineer, Senior Software Engineer, etc.).

## Competitive Advantages
- **Self-learning & adaptive**: Unlike traditional control systems that degrade over time, Gigaton’s AI continuously retrains and improves.
- **Explainable AI**: Builds operator trust by visualising the reasoning behind every control action – critical for safety in heavy industry.
- **Proven results**: Real-world deployments (e.g., Heidelberg Materials) show 2-4% fuel cost reduction and 33% reduction in process variability.
- **Fast deployment**: 8 weeks to go live, with a digital twin simulation environment for safer iteration.

## Strategic Focus
- **Autonomous plants**: Scaling its self-learning control system to more heavy industries (cement, steel, glass) to achieve fully autonomous, decarbonised production.
- **Industrial decarbonisation**: Leveraging AI to cut emissions at the source, targeting gigaton-scale impact.
- **Product expansion**: Continuing to refine the platform for additional process industries and expanding sales globally.

## Why Work Here
- **Culture**: “Runs on respect” – emphasis on technological craft, continual learning, and collaborative growth. Described as “sharpest minds, meet the cutting-edge” with a focus on world-changing impact.
- **Work model**: Hybrid (typically 2-3 days in office in London; equipment allowance for remote workers). Flexible hours with core hours and autonomy.
- **Perks**: 30 days holiday + bank holidays, 5% employer pension contribution, 17 weeks parental leave (13 weeks co-parent leave at full pay), personal learning budget of £500, company library, cycle-to-work and electric car scheme, mental health support, fresh fruit/snacks, regular socials and team events.
- **Engineering culture**: Focus on autonomous ownership, world-leading innovation, and solving the climate challenge. Tech stack includes frontier AI/ML applied to industrial control.

## Sources
1. [gigaton.co](https://gigaton.co/) – Company homepage and product overview
2. [gigaton.co/about](https://gigaton.co/about) – Mission, team, board, and investors
3. [gigaton.co/careers](https://gigaton.co/careers) – Careers page with perks, principles, and open roles
4. [gigaton.co/product](https://gigaton.co/product) – Product details, metrics, and case study
5. [uk.linkedin.com/company/gigaton-technologies](https://uk.linkedin.com/company/gigaton-technologies) – LinkedIn company profile (employee count, funding, growth)

## Other roles at Gigaton

- [Head of Engineering](https://feeny.ai/job/head-of-engineering-gigaton-london-ej8jw6n45pt6) — London, United Kingdom
- [Principal Cloud Engineer](https://feeny.ai/job/principal-cloud-engineer-gigaton-london-f5h9cn6ja665) — London, United Kingdom
- [Gigapool](https://feeny.ai/job/gigapool-gigaton-london-4k56atbk46b4) — London, United Kingdom
- [Solutions Engineer](https://feeny.ai/job/solutions-engineer-sona-new-york-pfaer8qp6jqh) — New York, NY
- [Solutions Engineer](https://feeny.ai/job/solutions-engineer-maxima-san-mateo-3anz3fxcptsh) — San Mateo, CA
- [Solutions Engineer](https://feeny.ai/job/solutions-engineer-infisical-united-states-4sq4czft0h4r) — United States
- [Solutions Engineer](https://feeny.ai/job/solutions-engineer-appdirect-united-states-ysaaxex0j6zt) — United States
- [Solutions Engineer](https://feeny.ai/job/solutions-engineer-beyondtrust-calgary-fpfkcc49bhxg) — Calgary, Canada / British Columbia, Canada
- [Solutions Engineer](https://feeny.ai/job/solutions-engineer-netskope-united-states-xr6mjhh2a8nn) — United States
- [Solutions Engineer](https://feeny.ai/job/solutions-engineer-legora-stockholm-qsrtzcrbc594) — Stockholm, Sweden