AI Engineering Leader — Scale Enterprise AI & MLOps

Centrica plc; Clewer Village; On-site; GBP 120,000 - 180,000; Full time

Job summary

Centrica plc is seeking an AI Engineering Manager to lead the design, development and deployment of enterprise-grade AI and LLM-powered solutions. You will mentor engineers, set engineering standards, and stay at the forefront of MLOps and AI governance.

You will partner with data scientists, product teams and business stakeholders to translate complex requirements into reliable, scalable AI systems while balancing innovation with operational reliability.

Qualifications

• Significant experience in AI Engineering, ML, or related technical discipline with production deployments.
• Experience leading and developing high-performing technical teams with a collaborative culture.
• Hands-on design/build/deploy of LLM-powered solutions at enterprise scale.
• Strong Python development skills and ML frameworks (PyTorch, TensorFlow, Scikit-learn).

Responsibilities

• Provide technical leadership to the AI engineering team with strong software engineering, MLOps, and responsible AI standards.
• Lead design, development, and deployment of AI applications, including LLM-powered solutions, with hands-on coding and architecture input.
• Support data scientists with model deployment, monitoring, and productionisation of AI solutions.
• Collaborate with data scientists, product owners, and stakeholders to translate business needs into AI solutions.
• Ensure operational excellence by embedding quality, security, reliability, and continuous improvement.

Skills

AI leadership

Python

PyTorch

TensorFlow

Scikit-learn

MLOps

LLM technologies

Cloud platforms

Azure

Databricks

CI/CD

DevOps

Stakeholder management

Education

Computer Science/Engineering/Data Science degree

Tools

CI/CD pipelines

Version control

Job description

Centrica plc is seeking an AI Engineering Manager to lead the design, development and deployment of enterprise-grade AI and LLM-powered solutions. You will mentor engineers, set engineering standards, and stay at the forefront of MLOps and AI governance.

You will partner with data scientists, product teams and business stakeholders to translate complex requirements into reliable, scalable AI systems while balancing innovation with operational reliability.