Machine Learning & AI Engineering Lead

End Date Sunday 20 September 2026

Salary Range £92,701 - £109,060

We support flexible working -

Flexible Working Options Hybrid Working, Job Share

Job Description

JOB TITLE:

Machine Learning & AI Engineering Lead

LOCATION:

London, or Manchester

HOURS:

Full-time - 35 hours WORKING PATTERN:
Our work style is hybrid, which involves spending at least two days per week, or 40% of our time, at one of our office sites. Colleagues with disabilities can be supported with workplace adjustments including hybrid working expectations in line with our Flexibility Works policy. Where role sits in Consumer… The Intelligent Customer Products (ICP) platform is a new CDO platform within Consumer Relationships.

It builds and scales capabilities including Conversational AI, AI Search, CoachAI and Super Agent to deliver trusted, personalised and effortless AI-powered customer experiences. ICP helps Lloyds create proactive, intelligent customer interactions that drive growth, improve customer satisfaction and reduce cost to serve, underpinned by the standards, governance and operational foundations needed to deploy AI safely at enterprise scale.

The Machine Learning & AI Engineering Lead is a senior technical leadership role within the Intelligent Customer Products (ICP) Platform, responsible for shaping and delivering AI-powered customer experiences across Lloyds Banking Group. The role will lead the design, engineering and industrialisation of machine learning, generative AI and agentic AI solutions that power strategic capabilities such as Conversational AI, AI Search and personalised customer engagement.

Drawing on strong expertise in AI engineering, cloud platforms and software delivery, the successful candidate will provide technical leadership, influence platform strategy, and mentor multidisciplinary teams to deliver secure, scalable and responsible AI solutions that create measurable value for customers and the Group.

• Lead the design, development and deployment of machine learning, LLM and Agentic AI solutions across the ICP Platform.
• Evaluate emerging AI technologies and drive adoption where they create measurable customer and business value.
• Establish engineering standards, patterns and reusable components for AI and ML solutions.
• Own the end-to-end AI delivery lifecycle from experimentation and prototyping through to production deployment and monitoring.
• Drive industrialisation of AI capabilities using MLOps and LLMOps practices.
• Ensure solutions meet performance, resilience, security and regulatory requirements.
• Partner with platform engineering teams to integrate AI capabilities into enterprise services and customer journeys.
• Build and govern foundation model, LLM, RAG and agentic AI solutions, including orchestration, automation, performance, evaluation and operations.
• Collaborate across Product, Architecture, Engineering, Data Science and business teams to translate outcomes into scalable AI/ML solutions and influence senior stakeholders.
• Ensure AI solutions meet Responsible AI, model risk, governance, explainability, fairness, monitoring, auditability, security and compliance requirements throughout the lifecycle.
• Lead, coach and build AI engineering capability through mentoring, knowledge sharing and an inclusive, high-performing culture.

• Deep experience designing, deploying, operating and optimising production-grade ML solutions at enterprise scale, including MLOps, monitoring and lifecycle management.
• Significant hands-on experience building foundation model and LLM applications, including RAG, vector search, agentic workflows, prompt engineering, evaluation, safety and responsible operational trade-offs.
• Strong Python software engineering background, with experience building scalable APIs, microservices and cloud-native AI applications in regulated enterprise environments using sound architecture, CI/CD and engineering practices.
• Strong experience delivering scalable, secure and cost-effective AI solutions on Google Cloud Platform, including Vertex AI, Big Query, Kubernetes and cloud-native architecture patterns.
• Proven ability to lead multidisciplinary engineering teams, influence senior stakeholders, coach talent and communicate complex technical concepts clearly to technical and non-technical audiences.

You'll work on market-leading AI products, solve meaningful customer problems at scale, and…