Staff UX Researcher - AI & Emerging Products

About the Role:
We’re looking for an experienced AI User Research Scientist to help shape the future of AI-driven security products at Auth0. This is not a traditional usability-focused role. You will be responsible for deeply understanding user needs, validating assumptions behind AI-powered solutions, and determining whether what we're building will be trusted, adopted, and ultimately deliver product-market fit.

In this highly strategic and cross-functional position, you'll work closely with engineers, AI researchers, product managers, and designers to ensure our LLM-based and agentic systems are grounded in human needs, secure by design, and aligned with business viability. This role requires a unique blend of user research expertise, market understanding, strategic foresight, and technical fluency in the AI product development process, which differs significantly from traditional software product development.

Key Responsibilities:

1. Strategic Product-Market Fit and Assumption Validation

• Lead research to test key assumptions around user behavior, trust, mental models, and willingness to adopt AI-powered security tools.
• Explore early-stage product concepts to assess user needs, barriers to adoption, and potential monetization strategies.
• Provide insights that shape long-term product direction and investment in AI capabilities.

1. Human-AI Interaction Research

• Design and execute studies that explore how users perceive, trust, and interact with LLMs, agents, and autonomous systems.
• Investigate failure modes, expectations, and control preferences in high-risk domains such as identity and security.
  Help product and engineering teams balance automation with human agency.

1. Cross-Functional Collaboration with AI & Engineering

• Partner with AI engineers, product managers, and designers to understand technical foundations (e.g., prompting strategies, model capabilities, hallucination risks).
• Translate user insights into meaningful guidance for cross-functional teams.
• Serve as the user-facing voice in discussions of model behavior, risk tradeoffs, and security boundaries.
• Able to engage confidently with AI/ML and engineering teams, asking sharp technical questions, understanding tradeoffs, and connecting user insights to feasibility and system behavior.

1. Research Methods & Experimentation

• Use mixed methods to uncover insights, from in-depth interviews and concept tests to survey design and behavioral analysis.
• Co-design experiments with PMs and data scientists to explore key hypotheses in live or staged environments.
• Identify signals in ambiguous or low-data contexts using creative methodological approaches.

1. Trust, Ethics & Safety

• Probe how users form trust with AI, especially in sensitive, security-first domains.
• Investigate concerns around data use, autonomy, explainability, and decision boundaries.
• Partner with compliance and responsible AI stakeholders to integrate ethical research practices.

1. Technical Fluency in AI Systems

• Understands how generative AI systems work at a foundational level, including LLM training, fine-tuning, evaluation, deployment, and common failure modes.
• Familiar with the factors that shape model behavior (e.g., prompting, guardrails, data pipelines, eval metrics, inference constraints, and human-in-the-loop patterns).
• Comfortable with major types of AI agents and how their architectures impact user interaction and control.
• Contributes meaningfully to discussions about limitations, hallucination risks, and human-AI interaction quality without needing to be an engineer.

1. Communication & Influence

• Synthesize complex insights into compelling narratives for both technical and non-technical audiences.
• Contribute to long-range strategic planning through research-backed perspectives.
• Serve as a trusted thought partner across product pillars and business units.

Required Experience & Skills:

• 6+ years of experience in research, ideally with a strong focus on AI, security, or enterprise platforms.
• Proven success in early-stage product research, product-market fit exploration, or strategic assumption testing.
• Foundational understanding of generative AI, model training workflows, and different agent architectures.
• Familiarity with LLM systems, agents, or AI-enhanced workflows — and ability to communicate their workings to non-technical stakeholders.
• Proficiency in a range of research methods (qual + quant), including surveys, concept testing, behavioral observation, and experiment design.
• Experience collaborating with cross-functional teams including engineering, AI/ML, design, and product.
• Deep curiosity, autonomy, and comfort working in ambiguous, 0→1 environments.

Preferred Experience:

• Prior experience in developer tools, identity, or security product environments.
• Understanding of model performance tradeoffs, hallucination risks, and AI system evaluation.
• Familiarity with pricing/value research, product desirability, or adoption analytics.

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