Staff UX Researcher

As a Staff UX Researcher at Okta, you will proactively construct and own an AI-forward research roadmap for key product pillars, operating at the intersection of Identity, Security, and Artificial Intelligence.

In this role, you'll drive both qualitative and quantitative methodologies to define user experiences for non-deterministic AI agents, automated workflows, and enterprise platforms. You'll leverage agentic tools and AI workflows internally to scale qualitative coding, synthesis, and research operations across the organisation.

Key responsibilities include:

• Driving product-shaping research to inform strategic and tactical product decisions
• Executing balanced mixed-methods research, combining qualitative depth and quantitative rigor
• Pioneering AI research operations, integrating AI tools and prompt engineering into daily practice
• Leading cross-discipline collaboration to drive clarity, alignment, and decision-making
• Solving complex problems, bringing stakeholders together to scope problems and collaborate on research
• Cultivating empathy, designing mechanisms to build up customer empathy and deep knowledge of users
• Telling high-impact stories, representing research to diverse audiences across the organisation

To be a fit for this role, you should have:

• 7+ years of hands-on UX research experience in complex B2B, developer, or enterprise software environments
• Demonstrated equal mastery across qualitative and quantitative research methodologies
• Active daily practice of AI tools and prompt workflows to streamline research processes
• Experience with products made for developers, administrators, or technical audiences
• Strong ability to plan, prioritise, organise, and solve complex problems independently
• Effective communication, storytelling, and alignment across all levels of leadership and cross-functional partners
• Master's or Ph.D. in Human-Computer Interaction, Cognitive Psychology, Computer Science, Data Science, Social Sciences, or equivalent industry experience

Nice-to-have skills include:

• Advanced quantitative toolkit: SQL, R or Python, cluster analysis, advanced statistical modeling, A/B testing
• AI systems and ops: human-in-the-loop UX evaluation, advanced prompt engineering for ops, agentic workflow evaluation, synthetic data validation