AI Engineering Manager

Description 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 .

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 practica