Principal UX Researcher, AWS Experience Analytics (EXA)
Posted Updated
Description
We are seeking a Principal Researcher who will shape how AWS understands, measures, and acts on the health of customer journeys at scale. AWS customers are shifting from console-based building toward AI-augmented, agent-primary, and autonomous workflows. With the wide adoption of agentic AI, customer journeys are changing fundamentally. You will set the strategic direction for how journey data becomes meaningful insight for stakeholders and partner teams, and establish EXA as the trusted voice on customer experience across AWS.
This is an individual contributor role. You will conduct research and operate at the intersection of customer stories, metrics, and strategy — translating complex journey signals into actionable intelligence that informs roadmaps across AWS service teams to improve customer experiences. You will mentor and develop researchers across levels, raise the bar for research quality and rigor across the organization, and contribute directly to scaling the team's capacity, methodologies, and mechanisms. You will bring creativity and a Learn and Be Curious mindset, lead through ambiguity, and drive alignment across engineering, science, and product teams with competing priorities.
The problems are genuinely interesting. With the wide adoption of agentic AI, customer needs and expectations are changing fundamentally — and there are many new problems we do not yet have answers to. We have far more questions than we can research, and that is where you come in.
Key job responsibilities
• Define and own the research strategy to inform how AWS measures, interprets, and acts on customer journey health — including what signals matter, how they stitch together to tell compelling stories, and what "meaningful insight" looks like.
• Convert complex journey signals into clear, actionable intelligence that shapes roadmaps and priorities across AWS service teams.
• Drive alignment and shared understanding across engineering, science, and product teams — navigating competing priorities and leading through ambiguity.
• Establish and elevate EXA as the trusted perspective on customer experience across AWS, ensuring journey insights reach the right stakeholders at the right time.
• Raise the bar for research quality, methodology, and storytelling across the organization — ensuring that every insight is grounded in evidence and designed to drive action.
• Mentor and develop researchers across levels, building the team's capacity to take on increasingly complex and ambiguous problems.
• Design and implement repeatable methodologies and mechanisms that allow the team to scale its impact beyond individual studies and projects.
• Develop prototypes and proof-of-concept tools using generative AI technologies to explore new ways of surfacing and communicating customer insights, or to scale research.
About the team
AWS Experience Analytics (EXA) turns customer understanding into products and intelligence that teams across AWS can use. We are building a unified customer lifecycle data platform and customer intelligence system that delivers deep customer understanding at scale. Our team approaches data both qualitatively and quantitatively, fusing customer insights with telemetry to tell actionable customer stories — insight is the critical layer that makes data meaningful.
This is an individual contributor role. You will conduct research and operate at the intersection of customer stories, metrics, and strategy — translating complex journey signals into actionable intelligence that informs roadmaps across AWS service teams to improve customer experiences. You will mentor and develop researchers across levels, raise the bar for research quality and rigor across the organization, and contribute directly to scaling the team's capacity, methodologies, and mechanisms. You will bring creativity and a Learn and Be Curious mindset, lead through ambiguity, and drive alignment across engineering, science, and product teams with competing priorities.
The problems are genuinely interesting. With the wide adoption of agentic AI, customer needs and expectations are changing fundamentally — and there are many new problems we do not yet have answers to. We have far more questions than we can research, and that is where you come in.
Key job responsibilities
• Define and own the research strategy to inform how AWS measures, interprets, and acts on customer journey health — including what signals matter, how they stitch together to tell compelling stories, and what "meaningful insight" looks like.
• Convert complex journey signals into clear, actionable intelligence that shapes roadmaps and priorities across AWS service teams.
• Drive alignment and shared understanding across engineering, science, and product teams — navigating competing priorities and leading through ambiguity.
• Establish and elevate EXA as the trusted perspective on customer experience across AWS, ensuring journey insights reach the right stakeholders at the right time.
• Raise the bar for research quality, methodology, and storytelling across the organization — ensuring that every insight is grounded in evidence and designed to drive action.
• Mentor and develop researchers across levels, building the team's capacity to take on increasingly complex and ambiguous problems.
• Design and implement repeatable methodologies and mechanisms that allow the team to scale its impact beyond individual studies and projects.
• Develop prototypes and proof-of-concept tools using generative AI technologies to explore new ways of surfacing and communicating customer insights, or to scale research.
About the team
AWS Experience Analytics (EXA) turns customer understanding into products and intelligence that teams across AWS can use. We are building a unified customer lifecycle data platform and customer intelligence system that delivers deep customer understanding at scale. Our team approaches data both qualitatively and quantitatively, fusing customer insights with telemetry to tell actionable customer stories — insight is the critical layer that makes data meaningful.