UX Researcher, Systems & AI Enablement

📍 Job Overview

Job Title: UX Researcher, Systems & AI Enablement

Company: Arizona State University (ASU)

Location: Scottsdale, Arizona, United States

Job Type: Full-time

Category: User Experience Research & Operations

Date Posted: 2026-04-24

Experience Level: Mid-Level (3+ years)

Remote Status: Hybrid (Requires reliable commute to Scottsdale, AZ)

🚀 Role Summary

• This hybrid role focuses on enhancing the UX research practice at ASU EdPlus by designing and implementing scalable systems and AI-enabled workflows (60% of the role).

• The position also involves hands-on user research, conducting generative and evaluative studies to inform product and systems development (40% of the role).

• Key responsibilities include building robust research infrastructure, integrating AI ethically, and optimizing the research lifecycle from intake to insight retrieval.

• Success in this role requires a blend of technical system design, AI governance, and rigorous human-centered research methodologies to drive efficiency and impact.

📝 Enhancement Note: The raw job description mentions "IT Support Specialist 2" and "IT Support Services" in the job profile and family sections, which seems to be a remnant from a different job posting and is not relevant to the UX Researcher, Systems & AI Enablement role. This enhanced description focuses solely on the UX Researcher aspects. The role is categorized under "User Experience Research & Operations" due to the significant emphasis on system design and operational efficiency within the research function.

📈 Primary Responsibilities

• AI Enablement & Systems Design:

  • Design, implement, and govern AI-enabled workflows and research systems to streamline the UX research lifecycle (intake, execution, repository, retrieval).
  • Develop and maintain tool integrations and automations across the research process.
  • Create standardized research operating components, including intake forms, study templates, tagging systems, reporting scaffolds, and reusable insight frameworks.
  • Build and manage repository architecture, taxonomies, and knowledge management structures for discoverability and reusability of insights.
  • Define approved AI use cases for the research team, including prompt libraries, documentation standards, and Quality Assurance (QA) frameworks.
  • Implement AI-assisted workflows to accelerate research preparation, synthesis, and documentation while maintaining human-led interpretation.
  • Ensure AI systems and workflows comply with research ethics, data privacy standards, and auditability requirements.
  • Evaluate AI tools and research systems through structured experimentation and ongoing UX research.
  • Design and conduct studies to assess the usability, adoption, and effectiveness of research tools and workflows, translating findings into actionable system improvements.
  • Measure operational health and impact through dashboards tracking efficiency gains, research capacity, insight reuse, and system adoption.

• UX Research Execution:

  • Conduct generative and evaluative research using qualitative and quantitative methods to understand user needs, behaviors, and motivations.
  • Develop comprehensive research plans, screeners, discussion guides, and success metrics aligned with product and systems goals.
  • Facilitate remote and in-person research sessions, including interviews, usability testing, workshops, and evaluative studies.
  • Analyze and synthesize research findings into clear, actionable insights for product managers, designers, engineers, and analysts.
  • Deliver executive-ready reports, dashboards, and insight summaries tailored for various stakeholders.
  • Ensure research findings are integrated into the knowledge base and reusable frameworks.
  • Partner with cross-functional teams (product, design, engineering, analytics) in agile environments to inform product direction and validate decisions.

• General Responsibilities:

  • Coordinate or assume other duties and projects as assigned.

📝 Enhancement Note: The responsibilities are meticulously divided into "AI Enablement & Systems Design" and "UX Research Execution" to clearly delineate the dual nature of the role, reflecting the 60/40 split mentioned in the job description. The "General Responsibilities" section is included as per the original posting.

🎓 Skills & Qualifications

Education:

Experience:

• Minimum of 3+ years of experience in technical product environments, specifically with B2B/B2C interfaces, AI-assisted workflows, or platform integrations.

• Minimum of 3+ years of experience integrating user research findings into digital product design and development processes.

• Demonstrated experience in designing and leading research projects from discovery through synthesis and reporting, both independently and collaboratively.

Required Skills:

• User Research Methodologies: Expertise in both qualitative (interviews, usability testing, ethnographic studies) and quantitative (surveys, analytics analysis) research methods.

• Systems Design & Architecture: Ability to design, implement, and maintain scalable systems, workflows, and knowledge management structures.

• AI Enablement & Governance: Understanding of AI use cases in research, prompt engineering basics, ethical AI deployment, and data privacy standards.

• Data Analysis & Synthesis: Proficiency in analyzing complex datasets, synthesizing findings, and translating them into actionable insights.

• Communication & Reporting: Excellent verbal and written communication skills, with the ability to create executive-ready reports, presentations, and dashboards.

• Collaboration & Facilitation: Strong ability to facilitate research sessions, design workshops, and collaborate effectively with cross-functional teams.

• Tool Proficiency: Familiarity with research platforms (e.g., Qualtrics, UserTesting.com), analytics tools (e.g., Google Analytics), and potentially project management or collaboration tools.

Preferred Skills:

• Design Thinking: Demonstrated familiarity with design thinking principles and facilitation of collaborative design sessions.

• Technical Product Experience: Specific experience with B2B/B2C interfaces, AI-assisted workflows, or platform integrations.

• Knowledge Management Systems: Experience designing and implementing repository architectures, taxonomies, and knowledge management structures.

• Agile Development: Experience working within agile or similar iterative development frameworks.

• Hands-on Design Experience: While not required, experience in UX design principles and processes is a plus.

• AI Tool Evaluation: Experience in evaluating and integrating new AI technologies relevant to research operations.

📝 Enhancement Note: The "Desired Qualifications" from the original posting have been incorporated into "Experience" and "Preferred Skills" sections. The "Required Skills" have been elaborated based on the responsibilities and the need for both research and systems expertise, integrating keywords like "Systems Design," "AI Governance," and "Knowledge Management."

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Impactful Case Studies: Showcase 2-3 detailed case studies demonstrating the impact of your UX research and/or systems design work. Each case study should clearly articulate the problem, your approach, the solutions implemented (especially systems/AI-related), and measurable outcomes.

• Systems Design Examples: Include examples of systems, workflows, or tools you have designed, implemented, or significantly improved. This could include research repositories, intake systems, automation scripts, or knowledge management frameworks.

• AI Integration Examples: If possible, provide examples of how you have integrated AI tools or methodologies into research processes, highlighting ethical considerations and effectiveness.

• Metrics & ROI: Clearly present how you measured the success of your initiatives, focusing on efficiency gains, increased insight reuse, adoption rates, or other relevant KPIs. Demonstrate the Return on Investment (ROI) or value generated.

• Process Documentation: Evidence of creating standardized operating procedures, templates, or documentation for research processes or systems.

Process Documentation:

• Candidates are expected to demonstrate experience in documenting and standardizing processes. This includes:
  • Workflow Design & Optimization: Showing how you have mapped, analyzed, and improved existing workflows for efficiency and effectiveness.
  • Implementation & Automation: Documenting the implementation of new tools, systems, or automated processes, including integration strategies.
  • Measurement & Analysis: Providing examples of how you have established metrics to track process performance and used data for continuous improvement.

📝 Enhancement Note: This section is tailored to the unique blend of UX research and systems/AI enablement. The emphasis is on demonstrating tangible results through portfolio pieces that highlight system design, AI integration, and process optimization, alongside traditional research impact.

💵 Compensation & Benefits

Salary Range:

Benefits:

• Comprehensive Healthcare: Access to various healthcare plans.

• Financial Security: Programs designed to support financial well-being.

• Retirement Planning: Robust retirement savings options.

• Family Resources: Support services for employees and their families.

• Tuition Reduction: Significant benefit for eligible ASU Employees, their dependents, and spouses, allowing for educational advancement.

• Exclusive Discounts: Employee discount programs.

Working Hours:

• Standard full-time hours, typically 40 hours per week. Flexibility may be available through alternate work schedules or hybrid remote arrangements, subject to approvals per ASU policy.

📝 Enhancement Note: The salary range is explicitly stated as provided in the input. Benefits are listed as per the original description. "Working Hours" are clarified to reflect the standard expectation while acknowledging potential flexibility.

🎯 Team & Company Context

🏢 Company Culture

Industry: Higher Education, EdTech, Digital Learning Solutions

Company Size: Large (Arizona State University is a major public research university with a vast number of employees and students across its campuses and online divisions). ASU EdPlus operates as a significant unit within this larger organization.

Founded: Arizona State University was founded in 1885. ASU EdPlus is a more recent initiative focused on digital education.

Team Structure:

• Product and User Experience Research Team: This role is part of a dedicated team focused on understanding and improving the user experience for ASU EdPlus's digital learning platforms and services.

• Reporting Structure: The UX Researcher, Systems & AI Enablement will likely report to a manager or director within the Product and User Experience Research team, potentially with oversight from leadership focused on operational efficiency and technology integration.

• Cross-functional Collaboration: The role requires close collaboration with product managers, UX designers, engineers, data analysts, and potentially AI specialists, as well as stakeholders across ASU EdPlus and the broader university.

Methodology:

• Data-Driven Decision Making: ASU EdPlus emphasizes using data and research to inform strategic decisions and product development.

• Human-Centered Design: A core philosophy is to prioritize the needs of learners and educators in the design and delivery of digital education.

• Scalable Delivery: Focus on designing and implementing solutions that can be scaled effectively to serve a large and diverse student population.

• Innovation & Experimentation: The culture encourages exploring new technologies, like AI, and experimenting with innovative approaches to improve educational outcomes.

Company Website: https://edplus.asu.edu/

📝 Enhancement Note: The company context is framed around Arizona State University's mission and EdPlus's specific role in digital learning. The "Methodology" section is inferred from the company's description and the nature of the role, focusing on data-driven, human-centered, and scalable approaches.

📈 Career & Growth Analysis

Operations Career Level: Mid-Level Specialist. This role bridges the gap between hands-on research and operational systems design, offering a unique career path for individuals interested in both deep user understanding and the infrastructure that supports research at scale.

Reporting Structure:

Operations Impact:

Growth Opportunities:

• Specialization in Research Operations: Develop deep expertise in building and managing research infrastructure, knowledge management, and AI enablement for research teams.

• Leadership in Systems Design: Grow into a lead role for designing and implementing complex research systems and platforms.

• AI Research Strategy: Become a go-to expert for leveraging AI responsibly and effectively within a research context.

• Cross-functional Influence: Gain experience influencing product strategy and development across multiple teams and projects.

• Mentorship: Opportunity to mentor junior researchers or contribute to the development of research best practices across the organization.

📝 Enhancement Note: This section emphasizes the unique hybrid nature of the role and its potential for career development at the intersection of UX research and operational efficiency. The "Operations Impact" highlights the strategic value of systematizing research.

🌐 Work Environment

Office Type: Hybrid, with a primary base at the ASU Scottsdale Innovation Center (SkySong). This environment is designed to be cutting-edge, collaborative, and conducive to innovation, housing a diverse business and research community.

Office Location(s):

Workspace Context:

• Collaborative Spaces: The SkySong center is designed to foster collaboration, likely offering meeting rooms, common areas, and flexible workspaces to encourage interaction.

• Technology & Tools: Employees will have access to the necessary technology and software to perform their roles, including research tools, analytics platforms, and potentially AI-powered systems.

• Team Interaction: Opportunities for regular interaction with the Product and User Experience Research team, as well as cross-functional colleagues, supporting knowledge sharing and team cohesion.

Work Schedule:

• While the role is hybrid, the expectation is to be present in the Scottsdale office reliably. The specific schedule and days in office will be subject to manager approval, aligning with ASU's flexible work policies. This allows for a balance between focused individual work and collaborative team engagement.

📝 Enhancement Note: The description highlights the modern, collaborative nature of the SkySong Innovation Center and connects it to the hybrid work model, emphasizing the balance between in-office and remote contributions.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A review of your resume, cover letter, and portfolio to assess alignment with the minimum and desired qualifications.

• Cover Letter Questions: Be prepared to thoughtfully answer the specific questions posed in the cover letter regarding AI in UX research and workflow improvement.

• Portfolio Review Session: A dedicated session where you will present selected case studies from your portfolio, explaining your methodologies, insights, and the impact of your work, particularly focusing on systems design and research operations.

• Technical/Skills Assessment: This may involve discussions about your experience with specific research methods, systems design principles, AI integration, and relevant tools.

• Behavioral & Situational Interviews: Questions designed to assess your problem-solving skills, collaboration style, ability to manage timelines, and how you approach challenges in a hybrid research/systems role.

• Final Interview: Potentially with senior leadership to discuss strategic alignment and overall fit.

Portfolio Review Tips:

• Highlight Systems & AI: Emphasize projects where you designed, implemented, or improved research systems, workflows, or leveraged AI. Quantify the impact wherever possible (e.g., "reduced synthesis time by 20%", "increased insight reusability by 30%").

• Structure Your Narrative: For each case study, clearly outline the problem, your unique contribution, the research or design process, key findings/solutions, and the measurable outcomes.

• Show, Don't Just Tell: Include visuals such as system diagrams, workflow maps, anonymized report excerpts, or dashboard mockups where appropriate to illustrate your work.

• Address the Prompt: Ensure your portfolio directly addresses the hybrid nature of the role, showcasing both research rigor and operational/systems thinking.

• Tailor to ASU EdPlus: Research EdPlus's mission and current initiatives to better contextualize your portfolio examples.

Challenge Preparation:

• Workflow Inefficiency Scenario: Be ready to discuss a hypothetical or past scenario where you identified workflow inefficiencies and outline your approach to diagnose, propose solutions (including potential system or AI enhancements), and measure success.

• AI Ethics in Research: Prepare to articulate your stance on ethical AI use in UX research, considering areas where AI is beneficial and where human oversight is critical.

• Systems Design Problem: You might be asked to sketch out a high-level design for a research repository or an automated research intake system, explaining your design choices.

📝 Enhancement Note: This section provides actionable advice tailored to the specific requirements of this unique role, emphasizing the need to showcase both research impact and systems/AI enablement capabilities in the portfolio and interview.

🛠 Tools & Technology Stack

Primary Tools (Likely to be used or evaluated):

• Research Platforms: Qualtrics, UserTesting.com, Maze, Lookback, SurveyMonkey.

• Analytics & Data Analysis: Google Analytics, Adobe Analytics, Tableau, Power BI, R, Python (for data analysis).

• Collaboration & Prototyping: Figma, Miro, Jira, Confluence, Asana, Microsoft Teams, Slack.

• AI Tools: Potentially generative AI platforms for summarization, transcription analysis, code generation (for scripts), and prompt engineering frameworks. Evaluation of new AI tools for research efficiency.

• Knowledge Management & Repository: Tools for building and managing searchable databases of research insights; custom-built solutions or platforms like Dovetail, Aurelius, or similar.

CRM & Automation:

• Familiarity with CRM concepts for understanding user segmentation and data flow, though direct CRM administration is unlikely the primary focus.

Integration & Data Management:

• Understanding of how to integrate different software tools to create seamless research workflows.

• Experience with data privacy and security protocols relevant to user data.

📝 Enhancement Note: This section lists common tools in UX research and operations, with a specific emphasis on AI tools and knowledge management systems, reflecting the core requirements of the role.

👥 Team Culture & Values

Operations Values:

• Curiosity & Risk-Taking: ASU EdPlus fosters a culture that encourages exploring new ideas and technologies, including AI, and not being afraid to experiment.

• Refusing the Status Quo: A drive to continuously improve processes and find better ways of working, especially in scaling research operations.

• Learner-Centricity: All efforts are geared towards improving the educational experience and success of students and educators.

• Excellence & Urgency: Striving for high-quality outcomes while maintaining a sense of urgency to deliver impactful solutions.

• Boldness & Problem-Solving: Encouraged to tackle complex challenges and propose innovative solutions.

Collaboration Style:

• Cross-functional Integration: Strong emphasis on working seamlessly with product managers, designers, engineers, and analysts to ensure research insights are integrated into development cycles.

• Open Communication: A culture that values open feedback, knowledge sharing, and transparent communication, especially within the research team and with stakeholders.

• Process Improvement Focus: Collaborative efforts to identify bottlenecks and inefficiencies in research workflows and systems, working together to implement improvements.

📝 Enhancement Note: Values are drawn directly from the "Department Statement" in the job description, rephrased to highlight their relevance to operations and research roles.

⚡ Challenges & Growth Opportunities

Challenges:

• Balancing Research Rigor with Systems Efficiency: The primary challenge is to design and implement systems that enhance efficiency and scalability without compromising the depth and integrity of human-centered UX research.

• Ethical AI Integration: Navigating the ethical considerations of using AI in research, ensuring data privacy, mitigating bias, and maintaining human oversight.

• Adoption of New Systems: Driving the adoption and effective use of new research systems and AI tools across the research team and with stakeholders.

• Measuring Impact: Developing robust metrics to quantify the impact of both research findings and systems improvements on operational efficiency and product outcomes.

• Keeping Pace with Technology: Continuously learning and adapting to the rapidly evolving landscape of AI and research technologies.

Learning & Development Opportunities:

• Specialized Training: Opportunities to deepen expertise in AI for research, advanced systems design, knowledge management, and specific research methodologies.

• Industry Conferences & Certifications: Potential support for attending relevant conferences or pursuing certifications in UX research, AI, or project management.

• Mentorship & Leadership: Opportunities to learn from experienced professionals within ASU EdPlus and potentially mentor junior team members as the role evolves.

• Exposure to Emerging Technologies: Working at the forefront of integrating AI into higher education's digital learning initiatives.

📝 Enhancement Note: Challenges are derived from the core responsibilities and the inherent complexities of the role. Growth opportunities are framed around skill development and career progression within research operations and AI enablement.

💡 Interview Preparation

Strategy Questions:

• Research Systems Design: "Describe a complex research workflow you've encountered. How would you design a system or leverage AI to make it more efficient, scalable, and insightful? What are the potential ethical considerations?"

• AI in UX Research: "Where do you see AI having the most significant positive impact in the UX research process, and where do you believe human oversight is absolutely critical? Provide specific examples."

• Measuring Operational Impact: "How would you define and measure the success of a new research repository system or an AI-powered synthesis tool? What key performance indicators (KPIs) would you track?"

• Stakeholder Management: "How would you gain buy-in from researchers and stakeholders for adopting new research systems or AI tools? How would you address resistance or concerns?"

Company & Culture Questions:

• "Based on your understanding of ASU EdPlus, how would your skills in systems design and AI enablement contribute to their mission of scaling digital teaching and learning?"

• "Describe a time you had to adapt your research or systems approach to fit within a larger organizational structure or culture. How did you ensure alignment?"

Portfolio Presentation Strategy:

• Focus on the "Systems & AI Enablement" Aspect: Dedicate a significant portion of your presentation to projects demonstrating your ability to design, implement, or improve research systems and workflows, especially those involving AI.

• Quantify Impact: Clearly articulate the measurable benefits of your work (e.g., efficiency gains, cost savings, improved insight discoverability, faster research cycles).

• Showcase Problem-Solving: For each case study, clearly define the problem, your analytical approach, the solutions you devised, and the results achieved.

• Explain Your "Why": Be ready to articulate the rationale behind your design choices for systems and workflows, and your decisions regarding AI integration.

• Prepare for Technical Deep Dives: Be ready to discuss the technical aspects of system design, integration challenges, and data management considerations.

📝 Enhancement Note: Interview questions are crafted to probe the dual nature of the role, specifically asking about the intersection of UX research, systems design, and AI enablement, with an emphasis on practical application and strategic thinking.

📌 Application Steps

To apply for this operations position:

• Submit your application: Utilize the provided link to the Workday Jobs Hub.

• Craft a compelling cover letter: Address the specific questions posed in the job description regarding AI in UX research and workflow efficiency. This is a critical opportunity to showcase your thinking.

• Tailor your resume: Highlight experience in systems design, AI enablement, workflow optimization, and user research. Use keywords from the job description and quantify achievements where possible.

• Prepare your portfolio: Curate 2-3 strong case studies that demonstrate your ability to design and implement research systems, leverage AI, and conduct rigorous user research. Ensure your portfolio clearly showcases impact and operational improvements.

• Research ASU EdPlus: Understand their mission, values, and approach to digital learning to better articulate your fit and contributions during interviews.

⚠️ 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.

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