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Must Haves:
* Strong experience with a range of UX research methods, including interviews, usability testing, surveys, and workshops
* Demonstrated experience conducting generative/ discovery research
* Hands-on experience using Generative AI tools in daily work, including to support research planning, analysis, synthesis, or sensemaking
* Ability to independently design, execute, and communicate research
* Experience using research analysis tools (e.g., Qualtrics, Dovetail, Excel, Rr)
* Working knowledge of qualitative and quantitative analysis methods
* Excellent communication and stakeholder collaboration skills
* Bachelor’s+ required (PHD preferred)
Plusses:
* Experience researching internal or enterprise tools
* Experience using Jobs to Be Done or similar outcome-focused frameworks
* Curiosity about human-AI interaction, trust, and adoption in AI-enabled systems
* Degree in human factors, psychology, anthropology, design, or a related field
Job Description:
In this role, you will focus on internal, employee-facing products powered by Generative AI, helping teams across the company work more efficiently and effectively.
You will work in fast-moving environments, partnering closely with product managers, designers, engineers, and AI practitioners to quickly understand employee needs and shape practical solutions. This role requires strong judgment, comfort with tradeoffs, and curiosity about how AI can both power products and accelerate research itself.
Initially, you will be the sole researcher supporting this work, balancing multiple initiatives while helping establish effective research practices for internal GenAI products.
Responsibilities
* Lead rapid discovery and evaluative research for internal, GenAI-enabled tools.
* Identify employee needs, pain points, and jobs to be done across roles and workflows.
* Select and apply appropriate research methods, balancing speed and rigor.
* Synthesize insights into clear, actionable guidance.
* Partner closely with product, design, engineering, and data science to frame problems and co-create solutions.
* Use analytics and system data to complement research.
* Apply AI tools to accelerate research planning, analysis, and synthesis.
* Manage multiple projects and priorities with minimal oversight.
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