Associate Director — AI UX Researcher

What you'll do

You'll own a portfolio of evaluative and foundational research across our enterprise AI products — our Everyday AI ecosystem, agent experiences, and the tooling that helps people choose the right AI for the job. You'll set the direction for how we measure trust, adoption, and value in AI products, not just usability.

Concretely, you will build and own the measurement frameworks that tell us whether our AI products are working — adoption, retention, task success, reliance, and value realised — and connect those signals to product decisions.

You'll design and run experiments (A/B and quasi-experimental) and longitudinal studies on how people adopt, rely on, and calibrate trust in AI systems, and where they over- or under-rely on them. You'll lead research at the scale enterprise AI generates, using AI-assisted analysis (topic modelling, product-feedback synthesis) to turn large volumes of behavioural and feedback data into direction. You'll pair that quantitative backbone with targeted qualitative work — generative and evaluative studies on agentic interfaces, where hand-off, oversight, correction, and delegation break down — so that scale and depth reinforce each other. And you'll partner with design, engineering, product, and data-science leaders to embed research into how AI products are built, mature the practice's methods and standards, and mentor researchers across the group.

What you'll bring

You're an experienced UX/product researcher with a strong quantitative and behavioural core. You lead with evidence and are quick to separate what the data shows from what people assume. Your strengths are experimental and quasi-experimental design, survey design and analysis, behavioural analytics, and building adoption and value-measurement frameworks for live products — ideally including AI, conversational, or other emerging-technology interfaces. You're fluent enough in foundational qualitative methods (generative interviewing, contextual enquiry, usability and concept evaluation) to run them yourself and to know when a question needs depth rather than scale — you choose the method that fits the question rather than defaulting to a favourite.

You're comfortable working with data-science and analytics partners, and you can work hands-on with research and analysis tooling. You're at home in the ambiguity of a fast-moving space — you can research products that change under your feet, and you're very pragmatic about rigour versus speed. You influence senior stakeholders with a clear, user's-eye point of view, and you communicate findings in a way that drives decisions and ownership rather than sitting in a report. You care about doing AI research the right way — ethically, honestly, and with the user's interests genuinely represented.

Qualifications — Essential

• Master's and/or PhD in a quantitative or research-intensive discipline — e.g. HCI, cognitive or experimental psychology, human factors, behavioural or data science, statistics, or a related field.
• Min 10 years of Substantial UX/product research experience, including leading mixed-methods research on live software products, with demonstrable depth in quantitative and behavioral methods.
• Proven experience designing and analysing experiments and surveys, and building measurement frameworks that shaped product decisions.

Desirable

• Experience researching or measuring AI, agentic, or conversational systems, and familiarity with AI evaluation approaches.
• Working knowledge of analysis tooling and languages (e.g. R, Python, SQL) and research-ops/analytics platforms.
• Experience using AI tools to scale research and analysis.
• Experience in a regulated or enterprise environment; line-management or mentoring experience.