AI Engineering Lead in Caversham

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