Requirements
- Proven experience leading research and development and/or software engineering activities in complex enterprise environments
- Recognised expertise in GenAI and Agentic AI technology, with experience of creating novel solution to real-world problems and successfully delivering AI systems to production
- Deep expertise in software engineering, application development and solution architecture, grounded in hands‑on experience
- Hands‑on experience using AI‑SDLC tooling (e.g. GitHub Copilot, Claude Code, Cursor) to accelerate individual and team engineering productivity
- Experience of working in a regulated environment and managing reliability, security, safety and explainability risks
- Experience of acting as a trusted advisor to executive leadership and influencing business strategy
- We know that great talent comes from many backgrounds. Whilst this job advert may reference specific years of experience, we recognise that skills are developed in many ways, so if you have relevant, transferable experience, we encourage you to apply
What the job involves
- We're looking for a Chief Engineer to lead our new Advanced AI Engineering team, reporting to the Group Director of Data & AI Architecture
- This role sits at the forefront of Agentic AI adoption within the Data & AI Unit of the Chief Technology Office, where we define and lead the Group’s Data and AI technology strategy and incubate new AI‑driven products and capabilities
- You'll be leading a team of applied research and development engineers to evaluate emerging AI technologies, build and deliver MVPs, and enable their transition into engineering at scale, with a focus on creating industry‑leading AI‑powered products and services that drive customer engagement and service excellence
- Acting as a senior leader and thought partner at Platform, CIO and Group level, you will be accountable for solving critical business and technology challenges, ensuring the delivery of high‑quality conversational AI across channels with strong safety, reliability and auditability, while shaping technical direction, driving applied research and prototyping, and working closely with senior collaborators and engineering teams to align AI innovation with business strategy and ensure effective adoption at scale
