AI Engineering Lead

Location: UK (Remote)
Compensation: £85,000 – £90,000 + up to 11% bonus
Contract: Permanent, Full-Time
Visa Sponsorship: Not available. Must have right to work in the UK without sponsorship.
Reports to: Head of AI
Split: Today, approximately 20% hands-on / 80% partner-led delivery accountability. Expected to shift toward 50/50 as the AI journey matures.

Who They Are

A major UK bank with board-level backing for AI. This isn't a side project. They're building a small, high-impact AI Centre of Excellence from the ground up - and they need a technical leader who can shape it.

Why This Role Is Special

• Greenfield opportunity: Early in the AI journey, with governance frameworks, lifecycles and controls still being built. You'll put your stamp on how this is set up.

• Board-level backing: AI has strong top-down support. You'll help explain solutions and tooling to senior leaders.

• Truly hybrid role: Not pure engineering, not pure strategy. A genuine player-coach blend of technical leadership and hands-on delivery.

• Incredible benefits: 10% matched pension, up to 11% bonus, private medical (family cover), 30 days holiday plus bank holidays, and life assurance.

• Grown-up working culture: Outcomes matter more than presenteeism. This role is fully remote.

What You'll Own

Technical Leadership & Delivery

• Lead design and delivery of AI solutions from concept through to production, working with a primary delivery partner and other partners, contractors and academic institutions.

• Be accountable for delivery outcomes, ensuring solutions are secure, scalable, compliant and aligned to Responsible AI principles.

• Shape technical direction, standards and best practice for AI engineering across the Group.

• Work with architecture, data, technology and business teams to identify and prioritise AI opportunities.

• Define the right build, buy and partner approach for AI solutions and services.

• Provide technical leadership across cloud-based AI platforms (Azure strategic, migrating from AWS), services and integrations.

• Support the growth of AI capability and adoption across the organisation.

Hands-On Engineering

• Get hands-on with code when needed, helping to build and deploy AI, Machine Learning and Generative AI solutions in production environments.

• Work with modern AI frameworks, LLMs, RAG, prompt engineering and vector databases.

• Ensure robust MLOps practices, APIs, data pipelines and modern software engineering disciplines are in place.

Strategic & Stakeholder Engagement

• Act as a thought leader, willing to challenge the business and drive new ways of working.

• Communicate clearly and confidently to senior leaders and board level, translating complex technical concepts into business language.

• Be a resilient change agent, pushing against colleagues who have done things the same way for years.

• Help establish engineering standards, frameworks and practices that enable AI solutions to be deployed securely, responsibly and at scale.

Must-Have

• Proven Production Experience: You have “lived it, breathed it.” Real commercial, production experience building and deploying AI/ML/GenAI solutions. Not just POC work or an academic pathway.

• Hybrid Technical & Strategic Skills: Deeply technical but able to present confidently to a board.

• Strong Engineering Foundation: Excellent Python and SQL skills. Terraform and CI/CD are must-haves.

• Regulated Environment Experience: You've worked in a corporate or regulated environment (financial services, public sector, insurance, etc.) and understand corporate governance.

• Consultancy Background (Preferred): Experience in consultancy is a strong fit - client engagement, stakeholder presentation, and balancing technical work with strategic advice.

• Thought Leadership & Resilience: Willing to challenge the status quo and drive new ways of working, even when faced with resistance.

• UK Right to Work: No sponsorship available.

Nice-to-Have

• Experience with Microsoft Azure, including Azure OpenAI, Azure AI Services, Azure Machine Learning and Azure Data Platform technologies.

• Knowledge of LLMs, RAG, prompt engineering, vector databases and modern AI frameworks.

• Experience with APIs, data pipelines, MLOps practices and modern software engineering disciplines.

• Experience managing partner-led delivery and a mix of onshore/offshore teams.

• Microsoft certifications (e.g., Azure AI Engineer, Azure Data Scientist).

The Process

1. 30-min Initial Screen: A light chat. A chance for you to ask questions and for us to get a feel for your background and communication style.

2. 1-hour Technical Interview: General technical questioning. No live coding or hackathon-style tasks. We'll explore your experience with AI/ML/GenAI, cloud platforms and modern engineering practices.

3. 1-hour Functional/Competency/Values Interview: Focused on values, your ability to lead and influence, and your experience in regulated environments.

4. Final Screen: A final conversation with a senior people leader for shortlisted candidates.

If you're a technically credible AI leader excited by the chance to build something from the ground up in a supportive, well-backed and genuinely flexible environment – apply now.