Associate Director, Product Development

Reporting & stakeholders: The role reports to the Pod Lead (PO) or Product Manager (as defined by the pod operating model). The UI/UX Designer works day-to-day with Business Analysts, engineers (AI/ML Engineers, Forward Deployed Engineers and front-end/full-stack engineers), the QA/Testing Lead and the Tech Delivery Lead to ensure designs are buildable, testable and delivered to schedule. They partner closely with Change & Adoption Lead to support adoption through intuitive journeys and, where needed, in-product guidance. The role also collaborates with the AI Solution Architect, data/platform teams and the Responsible AI Practitioner to ensure AI-enabled experiences are transparent, safe and aligned to Group AI standards. Where required, they engage in Risk, Compliance, Legal, Privacy and Information Security to ensure that experience design supports approvals, required disclosures and evidence expectations in a regulated environment. Scope & authority: The UI/UX Designer owns the end-to-end experience design for the pod's AI-enabled features, from journey mapping and interaction design through to UI pattern definition, prototyping and usability validation. They are accountable for producing clear, build-ready design outputs - clickable prototypes, annotated user flows, content guidance and detailed design specifications (components, states, accessibility notes and error handling) - so delivery teams can implement with pace and minimal rework. They have the authority to propose and recommend experience options and trade-offs, grounded in user evidence and delivery constraints, including decisions around automation vs human oversight, transparency vs friction and handling of AI uncertainty and failure modes. Final decisions on product scope, investment and priority remain with the Pod Lead, but the UI/UX Designer is accountable for ensuring experience risks are surfaced early, addressed through design, and aligned to design system standards, Responsible AI expectations and required governance/approvals. The role does not own product prioritisation or backlog decisions; it influences these through tested prototypes, user evidence and clear experience trade-offs This role exists to ensure AI-enabled solutions are designed around real user needs, are easy to use, and build trust - reducing rework and driving adoption. The UI/UX Designer brings clarity to complex AI behaviours through strong interaction design, validated journeys and production-ready specs. Target journey & product definition - Partner with Pod Lead/PO, BA and business stakeholders to define the target user journeys and key moments that AI will improve. Translate AI capabilities/constraints (confidence, latency, failure modes, monitoring) into clear experience patterns and user expectations. Ensure the experience supports end-to-end outcomes, not isolated screens (e.g., request → decision/support → follow-up → audit trail). UX discovery, research & testing standards - Plan and run lightweight discovery: stakeholder interviews, contextual enquiry, workflow walkthroughs and heuristic reviews. Define hypotheses and success measures for experience quality (task success, time-on-task, error rate, comprehension of AI outputs). Run rapid, repeatable usability testing on prototypes and early builds to validate journeys and UI patterns, synthesise findings, and drive iterative design improvements. UI patterns, prototyping & design specification - Create wireframes and high-fidelity prototypes for key flows, edge cases and system states (loading, low confidence, refusal, escalation). Provide build-ready design specifications covering components, states, empty/error cases, accessibility notes, responsive behaviour and content guidance to support build and QA. Promote reuse by applying approved design systems and reusable components/patterns; propose new components only when justified and document rationale for reuse. Design alignment to Responsible AI and control expectations - Embed “trust cues” and transparency: what the AI did, why, confidence/limits, and what users should do next. Design for safe use: appropriate human oversight, escalation paths, confirmation steps, and prevention of harmful/incorrect actions. Partner with Responsible AI Practitioner and control functions to ensure design supports required evidence and approvals (e.g., disclosures, decision records, audit trail touchpoints). Delivery collaboration & quality in execution - Work closely with engineers and QA to ensure designs are implemented as intended; join backlog refinement and sprint ceremonies as needed. Support design QA: verify UI implementation, interaction fidelity, accessibility compliance and content accuracy. Keep design artefacts current (journey maps, prototypes, specs) so decisions remain traceable and delivery stays unblocked. Adoption and change support (experience-led) - Partner with Change & Adoption Lead to ensure the solution is intuitive, learnable and supported by in-product guidance where needed. Identify friction points likely to reduce adoption and recommend design changes, onboarding or comms mitigations.