Staff UX Researcher - AI & Emerging Products

📍 Job Overview

Job Title: Staff UX Researcher - AI & Emerging Products

Company: Okta

Location: Toronto, Ontario, Canada

Job Type: Full-Time

Category: User Experience Research / AI Product Development

Date Posted: 2026-01-14

Experience Level: 5-10 Years (Mid to Senior Level)

Remote Status: Remote Eligible (for candidates in Toronto, Ontario, Canada)

🚀 Role Summary

• This role focuses on deeply understanding user needs and validating critical assumptions for AI-driven security products, particularly within emerging and LLM-based systems.

• It requires a strategic approach to ensuring product-market fit, user trust, and adoption of novel AI technologies within the identity and security domain.

• The position involves extensive cross-functional collaboration with AI researchers, engineers, product managers, and designers to translate user insights into actionable product strategies.

• A key aspect is researching human-AI interaction, including how users perceive, trust, and control autonomous and generative AI systems in high-risk environments.

📝 Enhancement Note: The "Staff" title indicates a senior individual contributor role, expected to operate with significant autonomy and influence strategic decisions. The emphasis on "Emerging Products" and "AI" signifies a focus on innovation and pioneering new product areas, requiring a researcher comfortable with ambiguity and 0→1 environments. The specific mention of Auth0, Okta's developer-focused identity platform, suggests the target users may include developers and security professionals.

📈 Primary Responsibilities

• Lead foundational research initiatives to validate core assumptions regarding user behavior, trust models, mental models, and adoption drivers for AI-powered security and identity solutions.

• Explore and define user needs and potential product-market fit for early-stage AI product concepts, including generative AI and agentic systems.

• Design and execute mixed-methods research studies to understand how users interact with, perceive, and trust AI systems, with a particular focus on LLMs and autonomous agents.

• Investigate critical human-AI interaction aspects such as user control preferences, understanding of AI failure modes, and the development of trust in security-sensitive contexts.

• Partner closely with AI/ML engineers, product managers, and designers to translate complex technical concepts (e.g., prompting strategies, model capabilities, hallucination risks) into user-centric insights and product guidance.

• Act as the primary advocate for the user in discussions concerning AI model behavior, risk trade-offs, security boundaries, and ethical considerations.

• Employ a variety of qualitative and quantitative research methodologies, including in-depth interviews, concept testing, surveys, and experimental design, to uncover actionable insights.

• Co-design and analyze experiments with product managers and data scientists to test key hypotheses and measure the impact of AI features in live or staged environments.

• Proactively identify and analyze user concerns related to data privacy, autonomy, explainability, and decision-making in AI systems, collaborating with compliance and responsible AI stakeholders.

• Synthesize complex research findings into compelling narratives, effectively communicating insights to both technical and non-technical audiences to drive strategic product decisions.

• Contribute to long-range product strategy and investment planning for AI capabilities through research-backed perspectives and thought leadership.

📝 Enhancement Note: The responsibilities highlight a strategic research function, moving beyond traditional usability testing to focus on market validation, trust, and the unique challenges of AI product development. The emphasis on "0→1 environments" and "ambiguous contexts" suggests a need for proactive problem-solving and the ability to generate insights with limited upfront data.

🎓 Skills & Qualifications

Education:

Experience:

• 6+ years of dedicated experience in user research, with a significant portion focused on AI, emerging technologies, security, or complex enterprise platforms.

• Proven track record of success in early-stage product research, validating product-market fit, and conducting strategic assumption testing for novel technologies.

Required Skills:

• User Research Expertise: Proficiency in a wide range of qualitative and quantitative research methods (e.g., in-depth interviews, usability testing, concept testing, ethnography, surveys, behavioral observation, experimental design).

• AI & ML Foundational Understanding: Foundational knowledge of generative AI systems, including LLM training workflows, evaluation metrics, common failure modes (e.g., hallucination), and prompting strategies.

• Human-AI Interaction: Ability to research and articulate user perceptions of trust, control, and mental models in relation to AI systems, especially autonomous and LLM-based agents.

• Cross-Functional Collaboration: Proven ability to partner effectively with engineering, AI/ML, product management, and design teams, translating user needs into actionable product requirements.

• Strategic Thinking & Problem Solving: Capacity to work in ambiguous, 0→1 environments, identify key research questions, and develop creative methodological approaches to uncover insights.

• Communication & Influence: Excellent written and verbal communication skills, with the ability to synthesize complex findings into compelling narratives for diverse audiences and influence product strategy.

• Technical Fluency: Comfort engaging in technical discussions with AI/ML and engineering teams, understanding system trade-offs, and connecting user insights to technical feasibility.

Preferred Skills:

• Prior experience specifically within developer tools, identity management, or cybersecurity product domains.

• Familiarity with pricing and value research, product desirability studies, or adoption analytics for technology products.

• Experience with AI system evaluation techniques, understanding model performance trade-offs, and AI ethics frameworks.

• Knowledge of data privacy regulations and compliance requirements relevant to AI and security products.

📝 Enhancement Note: The "Staff" level implies a need for deep expertise in research methodologies and a strong ability to mentor or guide less experienced researchers. The emphasis on technical fluency suggests that candidates with a background in computer science or a strong technical aptitude will be highly valued.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Demonstrated Research Impact: Showcase case studies that clearly illustrate how your research directly influenced product strategy, design decisions, or market validation for AI or complex technical products.

• Methodological Diversity: Present examples of using a range of research methods (qualitative and quantitative) to address complex research questions, particularly those involving novel technologies or ambiguous user needs.

• AI/ML Product Research Examples: Include specific projects focused on AI, machine learning, or complex software platforms where you explored user adoption, trust, human-AI interaction, or early-stage product concepts.

• Cross-Functional Collaboration Evidence: Highlight instances where your research insights were effectively translated and communicated to engineering, AI/ML, product management, and design teams, leading to tangible product improvements or strategic shifts.

• Ambiguity & 0→1 Experience: Showcase projects where you operated in undefined spaces, defined research objectives, and generated actionable insights from limited data or novel problems.

Process Documentation:

• Research Design & Execution: Clearly document the research questions, hypotheses, methodologies, recruitment strategies, and data analysis approaches used in your case studies.

• Insight Synthesis & Storytelling: Demonstrate your ability to synthesize findings into clear, compelling narratives that highlight the "so what" and the impact on product direction or user experience.

• Recommendations & Outcomes: Articulate the specific, actionable recommendations derived from your research and, where possible, provide evidence of the outcomes or impact of implementing those recommendations.

📝 Enhancement Note: For this specific role, portfolio items demonstrating research into user trust, adoption of new technologies, and understanding of complex technical systems (especially AI/ML) will be highly valued. Candidates should be prepared to discuss the nuances of researching AI behavior and its implications for product development.

💵 Compensation & Benefits

Salary Range: $127,000 - $191,000 CAD annually

Benefits:

• Comprehensive Health, Dental, and Vision Insurance plans.

• Retirement savings plan (RRSP) with employer matching.

• Healthcare Spending Account for additional medical expenses.

• Telemedicine services for convenient healthcare access.

• Generous Paid Time Off (PTO) and parental leave policies.

• Equity (stock options/grants) may be part of the compensation package.

Working Hours:

• Standard full-time role, typically 40 hours per week, with flexibility expected to meet project deadlines and research needs.

📝 Enhancement Note: The provided salary range is for candidates located in Canada. The company notes that the actual salary will depend on factors such as skills, qualifications, and experience. The mention of equity and bonus indicates potential for performance-based compensation beyond the base salary.

🎯 Team & Company Context

🏢 Company Culture

Industry: Technology (Identity and Access Management, Cybersecurity, Cloud Software)

Company Size: Okta is a large enterprise, indicated by its public company status and significant employee count, fostering a structured yet innovative environment.

Founded: Okta was founded in 2009, positioning it as an established leader in the identity space with a history of innovation and growth.

Team Structure:

• The role is within Auth0, Okta's developer-focused identity platform, suggesting a team composed of highly technical individuals.

• The UX Research team likely operates as a distributed function, embedded within product pods or working on strategic initiatives across multiple product pillars.

Methodology:

• Okta emphasizes a data-driven approach, integrating user research with product analytics and A/B testing to inform product decisions.

• The company values a culture of continuous learning and innovation, particularly in emerging areas like AI and security.

• There's a strong focus on understanding user needs and translating them into secure, scalable, and user-friendly solutions.

• The "AI & Emerging Products" focus suggests a methodology that embraces experimentation, rapid iteration, and a willingness to explore uncharted territory.

Company Website: https://www.okta.com/

📝 Enhancement Note: Okta's mission, "The World's Identity Company," underscores the critical nature of their products. The "AI & Emerging Products" group within Auth0 likely operates with a startup-like agility, focusing on future-proofing the platform and exploring new AI-driven capabilities.

📈 Career & Growth Analysis

Operations Career Level: Staff UX Researcher (Senior Individual Contributor)

This role represents a senior individual contributor position, expected to lead complex research initiatives, influence product strategy, and operate with a high degree of autonomy. It signifies a career path focused on deep expertise and strategic impact within UX research, particularly in specialized, high-growth areas like AI.

Reporting Structure:

• This role will likely report into a Director or Senior Manager of UX Research, potentially within the Auth0 product organization or a dedicated AI/Emerging Products research group.

Operations Impact:

• The research conducted by this role will directly shape the direction, design, and market success of Okta's AI-driven security products.

• Insights will be critical for validating the viability of new AI features, ensuring user adoption, and building trust in sensitive security contexts, thereby impacting revenue and competitive positioning.

Growth Opportunities:

• Specialization: Deepen expertise in AI/ML research, human-AI interaction, and security product development, becoming a go-to expert in these critical domains.

• Leadership: Transition into a Principal UX Researcher role, leading larger research programs, mentoring junior researchers, or potentially moving into a management track if desired.

• Strategic Influence: Gain significant experience in shaping long-term product roadmaps and influencing executive-level decisions through impactful research.

• Industry Exposure: Contribute to cutting-edge advancements in AI and identity security, potentially presenting findings at industry conferences or contributing to thought leadership.

📝 Enhancement Note: The "Staff" designation emphasizes the expectation of independent leadership and significant contribution to strategic initiatives. Growth will likely come from increased scope, complexity of problems tackled, and influence within the organization.

🌐 Work Environment

Office Type: Okta operates with a hybrid work model, and this role is designated as "Remote Eligible" for candidates located in Toronto, Ontario, Canada. This suggests a flexible work environment that prioritizes results over physical presence.

Office Location(s): While the role is remote-eligible in Toronto, Okta maintains offices globally, indicating a distributed workforce and potential for occasional travel for team meetings or company events.

Workspace Context:

• Collaborative & Remote-First: Expect a dynamic environment that supports remote collaboration through digital tools, video conferencing, and asynchronous communication.

• Technology-Rich: Access to Okta's robust technology stack, including advanced research tools, collaboration platforms, and AI/ML development environments.

• Cross-Functional Interaction: Opportunities to engage with diverse teams of engineers, researchers, product managers, and designers, fostering a rich exchange of ideas and perspectives.

• Focus on Innovation: The "AI & Emerging Products" team likely fosters an environment that encourages experimentation, intellectual curiosity, and pushing the boundaries of what's possible.

Work Schedule:

• Standard 40-hour work week is expected, with flexibility to accommodate research needs, cross-time zone collaborations, and project deadlines. The remote nature allows for greater autonomy in managing one's schedule.

📝 Enhancement Note: The remote eligibility for this role in Toronto highlights Okta's commitment to attracting talent globally and offering flexible work arrangements. Candidates should be comfortable with remote collaboration tools and proactive communication.

📄 Application & Portfolio Review Process

Interview Process:

1. Recruiter Screen: Initial conversation to assess basic qualifications, role understanding, and cultural fit.

2. Hiring Manager Interview: Deeper dive into experience, research philosophy, and strategic thinking, focusing on AI/emerging products and user research methodologies.

3. Portfolio Review & Presentation: Present selected case studies from your portfolio, demonstrating your research process, impact, and ability to communicate complex findings. This is a critical stage for showcasing your expertise in AI/ML research and human-AI interaction.

4. Cross-Functional Interviews: Meet with potential collaborators (e.g., AI Engineers, Product Managers, Designers) to assess your ability to work effectively in a cross-functional team and communicate insights to technical and non-technical audiences.

5. Staff-Level Interview / Executive Interview: A final discussion focused on strategic impact, leadership potential, and alignment with Okta's vision, often with a senior leader in research or product.

Portfolio Review Tips:

• Curate Strategically: Select 2-3 projects that best showcase your experience with AI/emerging products, human-AI interaction, security domains, and your ability to drive product strategy.

• Highlight Impact: For each project, clearly articulate the problem, your approach, the key insights, and the tangible impact your research had on the product or business. Use metrics where possible.

• Showcase AI Fluency: Be prepared to discuss your understanding of AI concepts, challenges in researching AI products (e.g., trust, explainability, hallucination), and how you navigated these complexities.

• Demonstrate Collaboration: Explain how you worked with AI/ML engineers, PMs, and designers, and how you translated technical constraints and user needs into actionable outcomes.

• Tell a Story: Structure your presentations to tell a compelling narrative about the problem, your journey, and the resolution or impact.

Challenge Preparation:

• AI Ethics & Trust Scenarios: Be ready to discuss hypothetical scenarios involving AI ethics, user trust, and safety in security products, and how you would approach researching these issues.

• Product Strategy Questions: Prepare to discuss how you would approach validating the market fit for a hypothetical AI-powered security feature or defining user needs for a new agentic system.

• Methodology Adaptation: Anticipate questions about how you would adapt traditional research methods for AI products or how you would design experiments to measure AI performance from a user perspective.

📝 Enhancement Note: The portfolio review is paramount for this role. Candidates must be able to clearly articulate their contributions to product strategy and demonstrate a deep understanding of the unique challenges and opportunities in researching AI-driven products.

🛠 Tools & Technology Stack

Primary Tools:

• Research Platforms: Tools for survey creation, participant recruitment, and data analysis (e.g., Qualtrics, SurveyMonkey, UserTesting.com).

• Collaboration Suites: Platforms for remote collaboration, documentation, and communication (e.g., Google Workspace, Microsoft 365, Slack, Confluence).

• Design & Prototyping Tools: Familiarity with tools used by design teams to understand prototypes and user flows (e.g., Figma, Sketch).

• Data Analysis Tools: Statistical software or BI tools for quantitative analysis (e.g., SPSS, R, Python libraries, Tableau).

Analytics & Reporting:

• Product Analytics: Experience with tools like Amplitude, Mixpanel, or Google Analytics to understand user behavior within products.

• Data Visualization: Tools for creating dashboards and reports (e.g., Tableau, Looker, Power BI) to communicate research findings and product metrics.

CRM & Automation:

• While not direct CRM roles, UX Researchers often interact with CRM data or systems to understand user segments and customer journeys. Familiarity with how data is managed in enterprise systems is beneficial.

• Understanding of workflow automation concepts is relevant given the focus on AI agents and automated systems.

📝 Enhancement Note: While specific tools aren't listed, proficiency in a wide array of qualitative and quantitative research tools, coupled with strong collaboration and data analysis software skills, is expected. Familiarity with tools used in AI/ML development environments would be a significant plus.

👥 Team Culture & Values

Operations Values:

• Customer Obsession: A deep commitment to understanding and advocating for user needs, ensuring products solve real problems and deliver value.

• Innovation & Curiosity: A drive to explore new technologies, question assumptions, and push the boundaries of what's possible, particularly in AI and security.

• Impact & Ownership: A focus on delivering measurable results and taking ownership of research initiatives from conception to influence on product strategy.

• Collaboration & Transparency: Openness to sharing insights, feedback, and working closely with cross-functional teams to achieve shared goals.

• Integrity & Responsibility: A commitment to ethical research practices, data privacy, and building secure, trustworthy AI systems.

Collaboration Style:

• Embedded & Agile: UX Researchers are often embedded within product teams, working in agile cadences to provide timely insights.

• Proactive & Consultative: Expect to proactively engage with product and engineering teams, offering research expertise and strategic guidance rather than waiting to be assigned tasks.

• Data-Informed: A collaborative approach that leverages both qualitative research insights and quantitative data to inform decisions.

• Cross-Functional Partnership: A style that emphasizes building strong relationships with engineers, PMs, and designers to ensure research is integrated seamlessly into the product development lifecycle.

📝 Enhancement Note: Okta's values emphasize a customer-centric, innovative, and collaborative approach. For this AI-focused role, a strong emphasis on ethical considerations, trust, and responsible AI development will be integral to the team's culture.

⚡ Challenges & Growth Opportunities

Challenges:

• Ambiguity in Emerging Tech: Researching novel AI technologies where user behaviors, mental models, and adoption patterns are not yet established.

• Defining Trust in AI: Investigating and influencing the complex factors that build user trust in AI systems, especially in high-stakes security scenarios.

• Bridging Technical Gaps: Effectively communicating complex AI/ML concepts to non-technical stakeholders and translating user needs into technically feasible solutions for AI engineers.

• Balancing Automation & Control: Researching how to best empower users with agency and control within increasingly automated AI systems without compromising security or efficiency.

• Rapid Iteration Cycles: Adapting research methodologies to keep pace with the fast-moving development cycles of AI products.

Learning & Development Opportunities:

• AI/ML Specialization: Gain deep expertise in researching cutting-edge AI technologies, including LLMs, generative AI, and agentic systems.

• Security Domain Expertise: Develop a nuanced understanding of the cybersecurity landscape and the unique user needs and challenges within identity management.

• Strategic Research Leadership: Grow into a role that significantly influences product strategy and roadmap development for critical AI initiatives.

• Mentorship & Knowledge Sharing: Opportunities to mentor junior researchers and contribute to the broader UX research community within Okta.

• Industry Engagement: Potential to attend or present at industry conferences focused on AI, UX, and security.

📝 Enhancement Note: The primary challenges lie in the inherent ambiguity of working with new AI technologies and the critical need to build user trust in sensitive security applications. Growth will stem from navigating these challenges and developing deep expertise.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you had to research a product or technology that was completely new to you and the market. How did you approach it?" (Focus on your process for defining unknowns and validating early assumptions.)

• "How would you approach researching user trust in an AI-powered security feature that makes autonomous decisions? What are the key questions you'd ask?" (Prepare to discuss methods for assessing trust, risk perception, and control.)

Company & Culture Questions:

• "Okta is 'The World's Identity Company.' How does this mission influence your approach to researching AI products in the security space?" (Connect your research philosophy to Okta's core mission and the importance of identity.)

• "How do you ensure your research findings are actionable for AI/ML engineers who may have different priorities or technical constraints?" (Highlight your collaboration and communication skills with technical teams.)

Portfolio Presentation Strategy:

• AI Impact Focus: For each case study, explicitly state the AI component or the complex technical aspect you researched, and the specific user insights you uncovered related to it.

• Trust & Adoption Narrative: Frame your projects to highlight how your research informed decisions around user trust, adoption barriers, and the overall value proposition of the product.

• Methodology Justification: Be ready to explain why you chose certain research methods, especially in the context of AI research, and how they helped overcome specific challenges.

• Quantify Outcomes: Where possible, use numbers to describe the impact of your research (e.g., "identified a critical adoption barrier that led to a 20% increase in feature usage after redesign," or "validated a key assumption that secured $X in future investment").

📝 Enhancement Note: Expect interviewers to probe deeply into your understanding of AI, your research process for novel technologies, and your ability to collaborate effectively with technical teams. Your portfolio should be the anchor for demonstrating these capabilities.

📌 Application Steps

To apply for this Staff UX Researcher position:

• Submit your application through the Okta careers portal via the provided URL.

• Curate Your Portfolio: Select 2-3 impactful projects that best showcase your experience in AI/emerging products, human-AI interaction, research impact, and cross-functional collaboration. Tailor your portfolio to highlight your ability to research complex, ambiguous technical domains.

• Optimize Your Resume: Ensure your resume clearly articulates your 6+ years of relevant research experience, specifically mentioning any work with AI, security, or enterprise platforms. Use keywords from the job description, such as "Generative AI," "LLM," "Human-AI Interaction," "Product-Market Fit," and "Trust."

• Prepare Your Case Studies: Practice presenting your selected portfolio projects, focusing on the problem, your unique research approach, key findings, actionable recommendations, and demonstrable impact. Be ready to discuss the nuances of researching AI systems and building user trust.

• Research Okta & Auth0: Familiarize yourself with Okta's mission, products (especially Auth0), and recent developments in AI. Understand their commitment to identity security and how AI fits into their strategy. This will help you tailor your responses and demonstrate genuine interest.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.