AI Engineering Lead

Overview

We are seeking an AI Engineering Lead to sit at the top of our client's delivery structure. This role bridges strategic leadership and hands-on delivery, providing day-to-day technical direction to a team of consultants and ensuring high-quality outcomes across multiple client environments.

You will remain deeply involved in solution design and build, while also shaping ways of working, mentoring engineers and consultants, and supporting pre-sales activity to secure and expand engagements.

Location & Salary

• Location: Hybrid, United Kingdom (UK-wide flexibility; occasional London presence a few days per month when required)
• Salary: £115,000 - £125,000 per year (DOE)
• Notice periods: Longer notice periods (including up to 6 months) can be considered for the right candidate

Key Responsibilities

• Lead end-to-end delivery of AI/ML and GenAI programmes: discovery, architecture, build, deployment and operationalisation.
• Act as the senior technical authority for clients, translating complex concepts into clear defined strategies for senior non-technical stakeholders.
• Own solution quality: engineering standards, code reviews, model governance, security, and delivery assurance.
• Provide technical leadership and coaching; build progression frameworks and mentoring for consultants.
• Drive pre-sales: shape propositions, run technical workshops, produce SOW inputs, estimates
• Partner with stakeholders across Data Services to deliver integrated outcomes (eg, BI and analytics alongside AI solutions).

Technical Scope

• Platform-agnostic engineering mindset; able to work across varied client stacks.
• Experience with cloud AI services and MLOps/LLMOps (eg, Azure AI Foundry, AWS SageMaker and/or Bedrock).
• Strong software engineering practices: Python, APIs, containerisation, CI/CD, IaC, testing, observability and production support.
• Modern ML/GenAI approaches: feature engineering, model training, evaluation, RAG, prompt engineering, guardrails, and responsible AI.
• Data engineering fundamentals: pipelines, data quality, governance, and working with structured/unstructured data.

Requirements

• Demonstrable hands-on technical delivery at senior level (not purely advisory).
• Strong senior stakeholder management; able to adjust communication style for technical and non-technical audiences.
• Proven experience leading multi-disciplinary teams and mentoring others.
• Pre-sales experience with measurable impact (pipeline contribution, proposals, or deal support).
• Right to work in the United Kingdom.

Interview Process

1. Introductory conversation
2. Technical experience deep dive
3. 90-minute case study with presentation