Full-Time

Solutions Engineer

Process Control

Updated on 9/4/2026

Gigaton

Gigaton

11-50 employees

AI-driven digital twin for industrial decarbonization

No salary listed

London, UK

Hybrid

Hybrid role with travel to deployment sites approximately one week per month.

Category
Solution Engineering (1)
Required Skills
Forecasting
Process Engineering
Machine Learning

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Requirements
  • Strong background in process or control engineering, ideally in cement, chemicals, energy, or heavy manufacturing.
  • Experience with advanced process control systems and process optimisation projects, including advanced process control, model predictive control, and proportional-integral-derivative systems.
  • Familiarity with industrial automation systems such as distributed control systems, programmable logic controllers, OLE for Process Control, and historian systems.
  • Comfort collaborating with operators, engineers, and data scientists to bridge industrial know-how with data-driven insights.
  • Ability to diagnose process instabilities and propose actionable solutions.
  • Ability to build credibility and trust in complex industrial environments.
  • Willingness to travel regularly to deployment sites, approximately 25%.
Responsibilities
  • Deploy and integrate Gigaton artificial intelligence 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 using advanced process control, model predictive control, and proportional-integral-derivative principles to bridge artificial intelligence recommendations with practical plant control systems.
  • Build trust and engagement with process engineers and operators by 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 to ensure repeatable, scalable, and high-quality rollouts across plants.
  • Provide field insights to Gigaton’s product and machine learning teams to shape the product roadmap and model development.
  • Work hands-on with teams during commissioning, testing, and optimisation phases at deployment sites.
  • Work through a kiln optimisation scenario balancing process stability, clinker quality, fuel use, and emissions to recommend an operating strategy during the technical interview.
  • Discuss and design control strategies for a high-temperature process using classical control methods such as proportional-integral-derivative, cascade, and feed-forward control, as well as advanced methods such as model predictive control, optimisation, and artificial-intelligence-assisted control.
Desired Qualifications
  • Understanding of artificial intelligence and machine-learning applications in process control, including forecasting, optimisation, and anomaly detection.
  • Experience implementing or tuning control systems and balancing process stability, quality, and energy efficiency.

Gigaton provides a SaaS platform that helps heavy industries cut emissions by building a digital twin for each plant using its historical and real-time data, with deep reinforcement learning to model processes. The Delta Zero AI layer suggests optimal operating parameters and can connect to a plant’s control systems for autonomous optimization without installing new hardware. It concentrates on cement, steel, and glass to lower fuel use, reduce operating costs, and drop CO2 emissions, with pilots showing up to 10% fuel savings and over 50 kilotonnes of CO2 reduced per plant per year. The aim is to scale industrial decarbonization by offering accessible optimization software to energy-intensive manufacturers worldwide.

Company Size

11-50

Company Stage

Series A

Total Funding

$47.1M

Headquarters

London, United Kingdom

Founded

2020

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Simplify Jobs

Simplify's Take

What believers are saying

  • June 2026 Series A raised $26 million, bringing total funding above $35 million.
  • Deployments at Adani Cement, Heidelberg Materials, Holcim, and Mannok show commercial traction.
  • Current customers report $1-3 million annual savings per plant and 30,000 tonnes CO2 cuts.

What critics are saying

  • Autonomous control software demands plant trust; one bad deployment can stall enterprise rollouts.
  • Incumbents like ABB, Siemens, and Honeywell own industrial control relationships and budgets.
  • If savings stay confined to a few plants, Gigaton remains a niche optimization vendor.

What makes Gigaton unique

  • Gigaton replaces control software for cement, steel, glass, and chemicals plants.
  • Its 2026 white paper with alcemy and CemAI validates a full cement-stack approach.
  • Series A backers Plural, 2150, and Semapa Next signal category credibility.

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Benefits

Company Equity

Flexible Work Hours

Paid Vacation

Growth & Insights and Company News

Headcount

6 month growth

-7%

1 year growth

-5%

2 year growth

-7%
World Cement
Jun 11th, 2026
Gigaton, alcemy, and CemAI publish white paper on AI's role across the cement production chain.

Gigaton, alcemy, and CemAI publish white paper on AI's role across the cement production chain. Gigaton, alcemy, and CemAI - Cement Intelligence, in partnership with World Cement, have released a new white paper titled "From quarry to lorry: how AI is solving cement's biggest production challenges." The guide brings together three companies operating across the cement and concrete production value chain to offer a practical, end-to-end roadmap for AI adoption. It covers the key prerequisites for successful deployment, including clean and connected data, domain expertise, and on-site leadership, alongside dedicated sections on predictive quality management, plant process optimisation, predictive maintenance, and driving long-term company-wide adoption. The white paper draws on real deployments with major producers and is aimed at plant managers, process engineers, quality specialists, and digital transformation leaders looking to move from AI ambition to measurable results. The release comes as Gigaton - formerly Carbon Re - announced a US$26 million Series A funding round, with deployments at Adani Cement, Heidelberg Materials, and Holcim already delivering over US$1 million in annual savings per plant. Visit alcemy for more information. Visit cemai for more information. Visit gigaton for more information. A podcast series for professionals in the cement industry featuring short, insightful interviews. Subscribe on your favourite podcast app to start listening today. Embed article link: (copy the HTML code below):

Tech Funding News
Jun 3rd, 2026
UCL and Cambridge spinout Gigaton raises $26M to autonomously control heavy industry, starting with cement — TFN

Gigaton (formerly Carbon Re) has raised $26M in a Series A led by Plural to scale AI-powered autonomous control systems for cement, steel, glass, and

GOV.UK
Sep 11th, 2023
AI for Decarbonisation Innovation Programme: Stream 2 successful projects

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