AI Engineering Manager

Centrica; City Of London; On-site; GBP 90,000 - 135,000; Full time

Job summary

Centrica is seeking an AI Engineering Manager to lead the design, delivery, and operation of enterprise-scale AI and LLM-powered solutions. You will mentor AI engineers, collaborate with data scientists, product teams and business stakeholders, and uphold software engineering, MLOps, and responsible AI standards.

You will report to the Director of AI & Data Science and shape Centrica's AI engineering capability, balancing innovation with reliability and governance while staying hands-on in

Qualifications

• Significant experience in AI Engineering, ML, or software development with production AI solutions.

Responsibilities

• Provide technical leadership to the AI engineering team, upholding strong standards in software engineering, MLOps, and responsible AI development.
• Lead the design, development, and deployment of AI applications, including LLM-powered solutions, with hands-on contribution to code, architecture, and decisions.
• Support data scientists with robust model deployment, monitoring, maintenance, and productionisation of ML/AI solutions.
• Collaborate with data scientists, product owners, business stakeholders, and data engineers to translate requirements into practical AI solutions.
• Ensure operational excellence across AI engineering by embedding quality, security, reliability, and continuous improvement into delivery.
• Mentor and develop AI engineers, fostering collaboration, learning, and growth.
• Stay informed about emerging AI, MLOps, and engineering practices to keep the team at the forefront of innovation.

Skills

AI Engineering

Team Leadership

LLM technologies

MLOps

Prompt engineering

Python

System design

Technical leadership

Program management

Mentoring

Stakeholder management

Analytical thinking

Responsible AI

Business acumen

Education

Bachelor's degree in Computer Science or related field

Certifications in AI/ML/Cloud/Data/MLOps (advantageous)

Tools

PyTorch

TensorFlow

Scikit-learn

Azure

Databricks

CI/CD

Version control

DevOps

Job description

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.

Qualifications and experience:

• 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.

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