Level

Centrica

AI Engineering Manager

AI in this role

pytorchtensorflowscikit-learndatabricks
prompt-engineeringragai-agentsml-opsai-safety

Join us, be part of more. 

We’re so much more than an energy company. We’re a family of brands revolutionising how we power the planet. We're energisers. One team of 21,000 colleagues that's energising a greener, fairer future by creating an energy system that doesn’t rely on fossil fuels, whilst living our powerful commitment to igniting positive change in our communities. Here, you can find more purpose, more passion, and more potential. That’s why working here is #MoreThanACareer. We do energy differently - we do it all. We make it, store it, move it, sell it, and mend it. 

AI Engineering Manager

As an AI Engineering Manager, you will lead the development and delivery of innovative AI solutions that help Centrica unlock value from data and emerging technologies. Combining technical leadership with hands-on engineering expertise, you will be responsible for guiding a team of AI Engineers in the design, development, deployment, and operation of scalable AI and Large Language Model (LLM) powered applications. Working closely with Data Scientists, Product teams, and business stakeholders, you will ensure AI products are secure, reliable, and built to enterprise standards.

Reporting to the Director of AI & Data Science, you will play a key role in shaping Centrica's AI engineering capability, driving best practice across software engineering and MLOps, and supporting the successful transition of machine learning models and AI solutions from experimentation into production. This is an exciting opportunity for a technically strong leader who enjoys developing people while remaining actively involved in architecture, solution design, and hands-on engineering delivery.


Responsibilities of the role:

  • Provide technical leadership and guidance to the AI engineering team, ensuring strong standards in software engineering, MLOps, and responsible AI development.
  • Lead the design, development, and deployment of AI applications, including large language model-powered solutions, while contributing hands-on to code, architecture, and technical decision-making.
  • Support data scientists with robust model deployment, monitoring, maintenance, and product ionisation of machine learning and AI solutions.
  • Collaborate with data scientists, product owners, business stakeholders, and data engineers to translate business requirements into practical AI solutions and deliver outcomes aligned to business priorities.
  • Ensure operational excellence across AI engineering by embedding quality, security, reliability, and continuous improvement into delivery.
  • Mentor and develop AI engineers, creating an environment that supports collaboration, continuous learning, innovation, and a growth mindset.
  • Stay informed about emerging AI, MLOps, and engineering practices so the team continues to operate at the forefront of innovation

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Here's what we’re looking for:

  • Significant experience in AI Engineering, Machine Learning, Software Development, or a related technical discipline, with a proven track record of delivering AI and machine learning solutions into production environments.
  • Experience leading, mentoring, and developing high-performing technical teams, creating a culture of collaboration, innovation, continuous improvement, and professional growth.
  • Hands-on experience designing, building, and deploying Large Language Model (LLM) powered solutions and generative AI applications at enterprise scale.
  • Strong Python development skills, with experience using machine learning frameworks such as PyTorch, TensorFlow, and Scikit-learn.
  • Deep understanding of AI Engineering, MLOps practices, and modern LLM technologies, including prompt engineering, Retrieval-Augmented Generation (RAG), AI agents, and model orchestration frameworks.
  • Experience implementing and managing MLOps capabilities, including model lifecycle management, deployment automation, experiment tracking, monitoring, governance, and machine learning pipelines.
  • Proven experience working with cloud platforms and modern engineering practices, including Azure, Databricks, CI/CD pipelines, version control, and DevOps methodologies.
  • The ability to design, build, deploy, and support scalable, secure, reliable, and production-grade AI solutions.
  • Strong technical leadership skills, with the ability to shape architecture, define engineering standards, guide technical decision-making, and drive delivery excellence.
  • Experience delivering complex technology programmes and balancing innovation with operational reliability and business priorities.
  • The ability to mentor and coach engineers, foster technical excellence, and build capability within the wider AI Engineering team.
  • Strong stakeholder management and communication skills, with the ability to engage and influence senior leaders, product owners, data scientists, engineers, and business stakeholders.
  •  Experience translating business requirements and challenges into practical technical solutions that deliver measurable commercial value.
  • Strong analytical thinking and problem-solving skills, with the ability to navigate ambiguity, manage competing priorities, and make sound engineering decisions.
  • An understanding of data governance, responsible AI principles, and the regulatory considerations associated with AI solutions.
  • Commercial awareness and an appreciation of how AI, data, and emerging technologies can drive business outcomes within a large, complex organisation.
  • A degree in Computer Science, Engineering, Mathematics, Data Science, or a related discipline, or equivalent practical experience.
  • Relevant certifications in AI, Machine Learning, Cloud Technologies, Data Engineering, or MLOps would be advantageous.

Why should you apply?   
  
We’re not a perfect place – but we’re a people place. Our priority is supporting all of the different realities our people face. Life is about so much more than work. We get it. That’s why we’ve designed our total rewards to give you the flexibility to choose what you need, when you need it, making sure that you and your family are supported not only financially, but physically and emotionally too. Visit the link below to discover why we’re a great place to work and what being part of more means for you.  
  
https://www.morethanacareer.energy/centrica

  

If you're full of energy, fired up about sustainability, and ready to craft not only a better tomorrow, but a better you, then come and find your purpose in a team where your voice matters, your growth is non-negotiable, and your ambitions are our priority.


Help us, help you. We would love for you to share any information about yourself throughout our recruitment process so that we can better understand you and help shape your journey.

How we rate this

AI Engineering Manager at Centrica rates 92 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Prompt EngineeringRAGAI AgentsML OpsAI SafetyPyTorchTensorFlowscikit-learn

Questions you could be asked

  1. How do you structure and test a prompt to get consistent output from a language model?
  2. How would you design a retrieval step so the model answers from real data instead of guessing?
  3. How do you decide when an AI agent can act on its own versus asking for approval first?
  4. How do you monitor a model once it's live, and how do you know it needs retraining?
  5. How do you think about the risk of an AI system in this kind of role failing silently?

Adapt your resume

  • List these exact terms on your resume: Prompt Engineering, RAG, AI Agents, ML Ops, and AI Safety. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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