AI Engineer Manager

Description

The company is one of the UK's leading AI and data businesses, with more than ten years of delivering production-grade AI solutions for government, healthcare, defence and commercial clients.

The company works with Microsoft and AWS, among others, on advanced AI and data solutions at citizen scale.

The AI and Data Practice has 150 people with expertise in machine learning, generative AI, agentic AI and data.

The practice is a pioneer in responsible AI and wrote the implementation guide for the UK government's AI Cyber Security Code of Practice.

The team partners with leading organisations to deploy AI that is ethical, secure and delivers measurable business value, and it is growing its AI capability.

Responsibilities

• Lead the delivery of advanced AI solutions built on state-of-the-art machine learning, generative AI and agentic AI.
• Drive the adoption of modern AI frameworks, AIOps practices and scalable cloud-native architectures.
• Lead technical decisions with senior stakeholders, agreeing architectural principles, strategic direction and system architecture.
• Represent the company and the wider industry as a technical leader, building a culture of innovation, continuous learning and engineering excellence.
• Manage, coach and develop a team, setting standards and policies, maintaining lasting customer relationships and building commercial awareness.
• Direct and lead your team as it solves hard problems together.

Requirements

• Hold at least a 2:1 degree in Computer Science, AI, Data Science, Statistics or a similar quantitative field.
• Have a track record of leading multi-disciplinary teams that delivered AI or ML solutions into production.
• Have shown technical leadership on AI delivery, covering architecture, product design principles and engineering excellence.
• Have hands-on experience with current AI engineering methods, including prompt engineering, retrieval-augmented generation (RAG), agentic AI and model evaluation.
• Monitor models with metrics such as precision, recall, NDCG and drift detection.
• Write strong Python and apply software engineering practices such as CI/CD, testing and code reviews.
• Have built solutions at scale on Azure and AWS, using containerisation and orchestration tools such as Docker and Kubernetes.
• Have expertise in data engineering for AI, working with large-scale, unstructured and multimodal data.
• Understand responsible AI, model interpretability and ethical considerations.
• Lead client projects, manage C-level stakeholders and set out requirements and architecture concepts with them.
• Have experience managing, coaching and developing junior team members and the wider community.

Conditions

Equal opportunities: the company welcomes applicants of every background and offers adjustments on request, with a private conversation to tailor the recruitment process.