Senior UX Designer

📍 Job Overview

Job Title: Senior UX Designer

Company: Thomson Reuters

Location: Eagan, Minnesota, United States (Hybrid)

Job Type: Full time

Category: User Experience (UX) Design, Product Design, AI/ML Product Development

Date Posted: September 09, 2026

Experience Level: 6+ years professional experience

Remote Status: Hybrid

🚀 Role Summary

• Lead the end-to-end design of next-generation AI-powered user experiences across a complex product ecosystem, focusing on intuitive and trustworthy workflows.

• Define how humans collaborate with AI, designing interactions, feedback loops, transparency, and control mechanisms for AI systems.

• Translate intricate AI model capabilities and limitations into clear, user-centered solutions, balancing innovation with responsible AI practices.

• Partner closely with product management, product engineering, and data science teams to build AI-driven features that enhance user outcomes and drive product adoption.

📝 Enhancement Note: This role is positioned at the intersection of traditional UX design and emerging AI/ML technologies, requiring a candidate who can navigate ambiguity and pioneer new interaction paradigms for AI systems. The emphasis on "responsible AI" and "trustworthy workflows" indicates a strategic focus on ethical design and user confidence in AI-driven products.

📈 Primary Responsibilities

• Lead the end-to-end design of AI-powered features, including agentic workflows, generative interactions, and human-in-the-loop systems.

• Translate complex model behaviors, data inputs, and system limitations into coherent UX patterns that foster user trust and product adoption.

• Prototype with AI/LLM models to evaluate user prompts, refine model responses, and inform product direction.

• Map and design collaboration patterns between users and AI, defining autonomous AI actions, human control points, and seamless handoffs.

• Create clear interaction flows that incorporate transparency moments, safety guardrails, override options, and robust recovery states.

• Partner with data science and engineering to shape model requirements, assess performance constraints, and align system behaviors with user needs.

• Collaborate with UX Research to conduct usability testing and AI-specific validation studies to understand user mental models, trust factors, and interaction expectations.

• Leverage qualitative and quantitative data to run evaluative studies for AI features, focusing on prompt/response quality, hallucination risk, and trust signals.

• Contribute to internal design standards for AI patterns, prompt design guidelines, evaluation criteria, and UX quality benchmarks.

• Identify new opportunities where AI can meaningfully improve user outcomes in collaboration with product and research teams.

• Communicate design decisions with clarity, influence senior stakeholders, and guide teams through ambiguous or evolving problem spaces.

• Leverage AI tooling and internal content standards to deliver clear, concise, and brand-aligned product experiences.

• Design accessible solutions and collaborate with the Accessibility team to ensure WCAG 2.1 AA compliance, utilizing AI checks alongside expert review.

📝 Enhancement Note: The responsibilities highlight a hands-on approach to AI design, requiring not just conceptualization but also direct interaction with AI models and research. The emphasis on defining "collaboration patterns" and "human-in-the-loop systems" suggests a focus on augmenting human capabilities rather than full automation.

🎓 Skills & Qualifications

Education: Bachelor's degree in Human-Computer Interaction (HCI), Design, Computer Science, Psychology, or a related field, or equivalent practical experience.

Experience: 6+ years of professional product design experience with a strong portfolio demonstrating end-to-end ownership of complex workflows.

Required Skills:

• Proven experience designing with AI or LLM technologies, including prompt design, generative UX, and evaluating model output quality.

• Strong interaction design skills with the ability to translate ambiguous AI behaviors into predictable, user-centered experiences.

• Familiarity with AI model behaviors and limitations, such as hallucinations, confidence levels, deterministic vs. probabilistic output, and data quality impacts.

• Ability to prototype using tools such as Figma, Python notebooks, model sandboxes, or no-code AI orchestration tools.

• Hands-on experience planning and executing end-to-end user research, including defining objectives, recruiting participants, moderating studies (interviews, usability tests, surveys, concept/validation), synthesizing insights, and translating findings into roadmap and design decisions.

• Deep systems-thinking skills and comfort designing across multiple layers: UI, data inputs, model constraints, and operational workflows.

• Experience collaborating with product management, product engineering, data science, product analytics, user research, content design, accessibility, and UX engineering in high-velocity, cross-functional teams.

• Strong communication and storytelling skills, with the ability to influence decisions and articulate the rationale behind design choices.

• Commitment to responsible AI principles, including transparency, fairness, and user empowerment.

• A growth mindset, comfort navigating ambiguity, and enthusiasm for experimenting with emerging technologies. Preferred Skills:

• Experience designing intuitive search, drafting, and review workflows, especially those involving complex knowledge structures or trust-critical decision moments.

• Comfort working with model-evaluation tooling, analytics dashboards, and prompt or version-management systems to understand and refine AI behavior.

• Strength in shaping information architecture for large-scale content ecosystems, including clear citation patterns, confidence signals, and quality indicators.

• Familiarity with domain-heavy environments (e.g., newsroom tooling, legal research, tax and compliance, risk and fraud, financial analysis) and the ability to translate complexity into usable experiences.

• Experience shipping zero-to-one products, iterating rapidly through ambiguity to test hypotheses, derisk bets, and accelerate product-market fit.

📝 Enhancement Note: The requirement for 6+ years of experience and a strong portfolio emphasizing "complex workflows" suggests this role is for a seasoned designer. The specific mention of AI/LLM experience, prompt design, and model evaluation is critical, differentiating it from a general UX role. The preference for domain-specific experience (legal, tax, etc.) indicates a focus on professional tools and workflows.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Showcase end-to-end design ownership of complex workflows, clearly illustrating your process from problem definition to final solution.

• Include case studies demonstrating experience with AI or LLM technologies, highlighting your approach to prompt design, generative UX, and model output evaluation.

• Present examples of interaction design for ambiguous AI behaviors, demonstrating how you simplified complexity into user-centered experiences.

• Detail your experience with user research for AI features, including methodologies used for evaluating mental models, trust factors, and interaction expectations.

• Illustrate your systems-thinking capabilities by showcasing designs that consider UI, data inputs, model constraints, and operational workflows.

• Provide examples of collaboration with cross-functional teams (Product, Engineering, Data Science, Research) on AI product development. Process Documentation:

• Demonstrate a clear understanding of the design process for AI-driven products, including user research, ideation, prototyping, and iterative testing with AI models.

• Present documentation of your involvement in shaping AI model requirements and aligning system behaviors with user needs.

• Show examples of how you’ve contributed to design standards, guidelines, or benchmarks for AI patterns and prompt design.

• Include case studies that highlight your ability to translate qualitative and quantitative data into actionable design decisions for AI features.

📝 Enhancement Note: The portfolio is expected to be heavily focused on AI-specific design challenges. Applicants should be prepared to detail their hands-on experience with AI models, prompt engineering, and evaluating AI outputs, not just the final UI. Systems thinking and cross-functional collaboration within an AI development context are key.

💵 Compensation & Benefits

Salary Range:

• For eligible US locations including New York City, San Francisco, Los Angeles, Irvine, CA; McLean, VA; Washington, DC: $117,700 USD - $218,600 USD per year.

• For other eligible US locations: $102,200 USD - $189,800 USD per year. Benefits:

• Market competitive health, dental, and vision insurance programs.

• Disability and life insurance programs.

• Competitive 401k plan with company match.

• Flexible vacation policy.

• Two company-wide Mental Health Days off.

• Access to the Headspace app.

• Sabbatical leave.

• Parental leave.

• Tuition reimbursement.

• Employee incentive programs.

• Commuter benefits.

• Adoption & Surrogacy Assistance.

• Employee Stock Purchase Plan.

• Optional hospital, accident, and sickness insurance (employee-paid).

• Optional life and AD&D insurance (employee-paid).

• Flexible Spending and Health Savings Accounts.

• Fitness reimbursement.

• Access to Employee Assistance Program.

• Group Legal Identity Theft Protection (employee-paid).

• Access to 529 Plan.

Working Hours: 40 hours per week (standard full-time). The company emphasizes flexibility and work-life balance through policies like "Flex My Way" and "Work from Anywhere" for up to 8 weeks per year.

📝 Enhancement Note: The salary range provided is comprehensive and location-dependent, reflecting Thomson Reuters' commitment to competitive compensation. The extensive list of benefits underscores a strong focus on employee well-being, work-life integration, and professional development, which are attractive to experienced professionals. The inclusion of "Flex My Way" and "Work from Anywhere" policies highlights a modern approach to work flexibility.

🎯 Team & Company Context

🏢 Company Culture

Industry: Information Services, Technology, Media, Legal Tech, Tax & Accounting Software. Thomson Reuters is a global leader in providing trusted content and technology solutions for professionals.

Company Size: 26,000+ employees globally. This large size indicates a mature organization with established processes, ample resources, and opportunities for internal mobility, while also potentially requiring agility to innovate.

Founded: Thomson Reuters has a long history, tracing roots back to the 19th century, evolving through mergers and acquisitions to become a modern information giant. This heritage suggests stability and deep industry expertise.

Team Structure:

• The UX team operates within a cross-functional product development structure, collaborating closely with Product Management, Product Engineering, Data Science, Product Analytics, User Research, Content Design, Accessibility, and UX Engineering.

• The Senior UX Designer is expected to influence product strategy and guide teams, suggesting a leadership role within design initiatives.

• Collaboration is likely structured around agile methodologies, with a focus on iterative development and rapid feedback loops. Methodology:

• Data-driven decision-making is paramount, utilizing qualitative and quantitative data from user research and product analytics to inform design.

• A strong emphasis is placed on responsible AI principles, ensuring that AI solutions are ethical, transparent, and user-empowering.

• The company embraces experimentation and a "Learn Fast" mentality, particularly in the context of emerging technologies like AI.

• Design processes incorporate accessibility standards (WCAG 2.1 AA) from the outset, ensuring inclusive product experiences.

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

📝 Enhancement Note: Thomson Reuters' position as a trusted information provider in critical professional sectors means the UX team operates with high stakes regarding accuracy, reliability, and user trust, especially when integrating AI. The company culture emphasizes innovation within a structured, ethical framework.

📈 Career & Growth Analysis

Operations Career Level: Senior UX Designer. This level signifies a seasoned professional expected to lead complex design initiatives, mentor junior designers, and influence product strategy. The role demands significant autonomy and the ability to drive projects from conception to launch with minimal supervision.

Reporting Structure: While not explicitly detailed, a Senior UX Designer typically reports to a UX Manager, Director of Product Design, or a Head of Product. They will work closely with Product Managers and Engineering Leads, often acting as the primary design voice for their product area.

Operations Impact: The Senior UX Designer's work directly impacts the usability, adoption, and perceived value of AI-powered features within Thomson Reuters' professional software. By creating intuitive and trustworthy AI experiences, they contribute to user efficiency, decision-making accuracy, and ultimately, customer satisfaction and retention, which are critical for revenue generation in their target markets.

Growth Opportunities:

• Specialization: Deepen expertise in AI/LLM UX design, becoming a go-to specialist within the organization for AI-driven product innovation.

• Leadership: Transition into a Lead UX Designer or UX Manager role, overseeing design teams and strategy for larger product portfolios.

• Cross-functional Advancement: Move into Product Management or Product Strategy roles, leveraging deep user and technology understanding to shape product roadmaps.

• Mentorship: Guide and develop junior designers, contributing to the overall growth and skill development of the UX team.

• Continuous Learning: Engage with emerging AI technologies, attend industry conferences, and pursue certifications to stay at the forefront of UX and AI innovation.

📝 Enhancement Note: This senior role offers significant opportunities for impact and career progression, particularly in the high-demand field of AI UX design. The potential to shape "zero-to-one" products and influence strategic direction is a key growth driver.

🌐 Work Environment

Office Type: Hybrid. Employees are expected to work from an office location some days per week, balancing this with remote work flexibility. This model aims to foster collaboration and team cohesion while allowing for personal flexibility.

Office Location(s): Eagan, Minnesota; Frisco, Texas; New York, New York; Ann Arbor, Michigan. These locations offer professional office environments equipped to support collaborative work.

Workspace Context:

• The workspace is designed to facilitate collaboration among cross-functional teams, encouraging interaction between designers, product managers, engineers, and data scientists.

• Access to modern design tools, prototyping software, and potentially direct access to AI/LLM sandboxes or development environments.

• Opportunities for informal brainstorming, design critiques, and knowledge-sharing sessions within the UX team and broader product development groups.

Work Schedule: The standard work schedule is 40 hours per week. The company emphasizes flexibility through "Flex My Way" and "Work from Anywhere" policies (up to 8 weeks/year), allowing employees to manage their schedules and work locations effectively while ensuring business needs are met.

📝 Enhancement Note: The hybrid model and multiple office locations provide flexibility. The emphasis on collaboration in the workspace context is crucial for a role that requires close interaction with diverse technical and product teams, especially in the iterative process of AI development.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: HR or recruiter call to assess basic qualifications, role fit, and salary expectations.

• Portfolio Review & Initial Interview: A deeper dive into your portfolio, focusing on specific case studies, your design process, and your experience with AI/LLM technologies. This may involve a presentation of 1-2 key projects.

• Design Challenge/Case Study: A practical exercise, potentially involving a hypothetical AI design problem. This could be a take-home assignment or a live working session to assess your problem-solving skills, design thinking, and ability to articulate your approach.

• Cross-functional Interviews: Meetings with Product Management, Engineering, Data Science, and UX Research stakeholders to evaluate collaboration style, technical understanding, and ability to integrate AI concepts into broader product strategies.

• Hiring Manager/Senior Leadership Interview: Final discussion to assess strategic thinking, leadership potential, cultural fit, and overall alignment with Thomson Reuters' vision.

Portfolio Review Tips:

• Curate Strategically: Select 3-4 projects that best showcase your end-to-end design process, particularly those involving complex problem-solving, AI/LLM integration, or innovative interaction design.

• Quantify Impact: For each project, clearly articulate the problem, your role, your process, the challenges faced, and the measurable outcomes or impact achieved. Use metrics where possible (e.g., user satisfaction, efficiency gains, adoption rates).

• Highlight AI Expertise: Explicitly detail your experience with AI/LLM technologies, prompt design, model evaluation, and responsible AI principles. Show how you translated AI capabilities and limitations into user-centric designs.

• Showcase Systems Thinking: Demonstrate your ability to design holistic experiences that consider the UI, data flows, model constraints, and user workflows.

• Explain Your "Why": Be prepared to articulate the rationale behind your design decisions, especially how they address user needs and business objectives within the context of AI.

Challenge Preparation:

• Understand AI Nuances: Brush up on common AI/LLM concepts, potential pitfalls (e.g., hallucinations), and best practices for prompt design and interaction.

• Practice Problem Decomposition: Be ready to break down a complex, potentially ambiguous problem into smaller, manageable parts.

• Articulate Trade-offs: Anticipate questions about design trade-offs, especially those involving balancing AI capabilities with user trust, safety, and usability.

• Prepare for Collaboration: Think about how you would collaborate with data scientists, engineers, and product managers on an AI design project.

📝 Enhancement Note: The interview process is designed to thoroughly assess not only traditional UX skills but also specialized knowledge in AI/LLM design. The portfolio review is critical, and candidates should be prepared to present detailed case studies that highlight their direct experience with AI technologies and their ability to navigate the unique challenges they present.

🛠 Tools & Technology Stack

Primary Tools:

• Prototyping & Design: Figma (primary tool expected), potentially Sketch, Adobe XD.

• AI/LLM Interaction: Python notebooks, model sandboxes, no-code AI orchestration tools (specific tools may vary but the ability to use them is key).

• Collaboration: Jira, Confluence, Slack, Microsoft Teams.

Analytics & Reporting:

• User Research Platforms: Tools for usability testing, surveys, and participant recruitment (e.g., UserTesting.com, Qualtrics, SurveyMonkey).

• Product Analytics: Tools for tracking user behavior and feature adoption (e.g., Amplitude, Google Analytics, Pendo).

• Data Visualization: Tools may be used to understand model performance and user interaction data (e.g., Tableau, Power BI, internal dashboards).

CRM & Automation:

• While not directly a CRM role, understanding how UX designs integrate with CRM and marketing automation platforms for user journey optimization may be beneficial.

📝 Enhancement Note: Proficiency in Figma is almost certainly expected for a Senior UX Designer. The critical differentiator here is the demonstrated ability to work with and prototype using AI/LLM technologies, which may involve scripting (Python) or specialized sandboxing environments. Familiarity with product analytics and user research tools is standard for UX roles.

👥 Team Culture & Values

Operations Values:

• Obsess over our Customers: A deep understanding of user needs and a commitment to delivering solutions that provide tangible value and solve real-world problems for professionals.

• Compete to Win: Striving for excellence in product design and user experience to maintain a competitive edge in the market.

• Challenge (Y)our Thinking: Embracing new ideas, questioning assumptions, and fostering a culture of continuous improvement, especially relevant with rapidly evolving AI technologies.

• Act Fast / Learn Fast: An agile and iterative approach to product development, prioritizing rapid experimentation and learning from both successes and failures.

• Stronger Together: Emphasizing collaboration, knowledge sharing, and mutual support across diverse teams to achieve collective goals.

Collaboration Style:

• Cross-functional Integration: A highly collaborative approach, working closely with Product Management, Engineering, Data Science, and Research to co-create AI-powered products.

• Data-Informed Design: A reliance on data and research to guide decisions, coupled with the ability to translate complex AI concepts into user-friendly experiences.

• Open Communication: Encouraging clear, honest, and constructive feedback among team members to refine designs and improve processes.

• Proactive Problem-Solving: A culture where team members are empowered to identify challenges and proactively develop solutions, particularly in the ambiguous space of AI design.

📝 Enhancement Note: The company values align well with the demands of designing AI products. The "Challenge (Y)our Thinking" and "Act Fast / Learn Fast" values are particularly relevant for a role exploring new AI paradigms. The emphasis on collaboration is crucial for integrating AI effectively across complex professional software.

⚡ Challenges & Growth Opportunities

Challenges:

• Navigating AI Ambiguity: Designing for AI systems that are inherently probabilistic, can produce unexpected outputs (hallucinations), and have evolving capabilities requires a high tolerance for ambiguity and a robust iterative process.

• Building User Trust in AI: Instilling confidence in AI-driven features is paramount. This involves designing for transparency, explainability, and user control, especially in critical professional workflows.

• Translating Technical Complexity: Effectively translating the intricacies of AI models, data inputs, and system constraints into simple, intuitive user experiences for professional users.

• Defining "Responsible AI" in Practice: Implementing ethical design principles for AI requires continuous learning and careful consideration of fairness, bias, and user empowerment within specific product contexts.

• Zero-to-One Product Development: For new AI features, the challenge lies in validating hypotheses, derisking bets, and achieving product-market fit in a rapidly evolving technological landscape.

Learning & Development Opportunities:

• AI UX Specialization: Deepen expertise in AI UX patterns, prompt engineering, and evaluating AI model performance through hands-on project work and specialized training.

• Industry Trends & Conferences: Access to resources and opportunities to attend leading UX and AI conferences to stay abreast of the latest advancements.

• Mentorship & Leadership Development: Opportunities to mentor junior designers and potentially step into leadership roles within design projects or teams.

• Cross-Domain Exposure: Gain exposure to various professional domains (legal, tax, compliance) and understand how AI can solve unique challenges in each.

• Skill Enhancement Programs: Utilize company-provided "Grow My Way" programming and tuition reimbursement for formal learning and skill development.

📝 Enhancement Note: The challenges presented are intrinsic to pioneering AI product design. The growth opportunities are substantial, offering a path for deep specialization in AI UX and potential leadership within a leading information services company.

💡 Interview Preparation

Strategy Questions:

• "Describe a complex AI feature you designed. What were the key challenges in translating the AI's capabilities and limitations into a user-friendly experience, and how did you address them?" (Focus on your process, AI-specific considerations, and user outcomes).

• "How do you approach building user trust in AI-powered systems, especially in a professional context where accuracy and reliability are critical?" (Discuss transparency, explainability, control mechanisms, and your experience with trust-building design patterns).

• "Imagine we are developing an AI assistant for legal professionals. What are the first three things you would investigate or design to ensure its effectiveness and adoption?" (Demonstrate your problem-decomposition skills, understanding of professional workflows, and AI design thinking). Company & Culture Questions:

• "How do Thomson Reuters' values, such as 'Challenge (Y)our Thinking' and 'Act Fast / Learn Fast,' influence your approach to designing with emerging AI technologies?" (Connect your work style to company values).

• "Describe a time you had to collaborate closely with data scientists or engineers on a complex technical project. How did you ensure effective communication and alignment?" (Highlight your cross-functional collaboration skills).

• "How do you ensure your designs are inclusive and accessible, particularly when dealing with new AI interfaces and potential biases?" (Showcase your commitment to responsible and accessible AI design). Portfolio Presentation Strategy:

• Structure Your Narrative: For each case study, clearly outline the problem, your role, the project goals, your design process (emphasizing AI-specific steps), the solutions you developed, and the impact achieved.

• Show, Don't Just Tell: Use mockups, prototypes, flow diagrams, and research findings to illustrate your design decisions and their rationale. For AI projects, include examples of prompts, AI responses, and how you designed for iteration or correction.

• Emphasize AI Nuances: Explicitly discuss how you handled AI model behaviors, limitations, prompt design, and evaluation. Highlight any use of AI sandboxes or prototyping tools.

• Quantify Impact: Wherever possible, present metrics that demonstrate the success of your designs (e.g., increased task completion, improved efficiency, higher user satisfaction scores).

• Be Ready for Deep Dives: Anticipate questions about specific design choices, the trade-offs you made, and how you validated your solutions with users and stakeholders.

📝 Enhancement Note: Preparation should focus on articulating a strong design process, especially as it applies to AI, and demonstrating an understanding of user trust, responsible AI, and cross-functional collaboration within a professional context. The portfolio presentation is a key component, so candidates should practice explaining their AI design contributions clearly and concisely.

📌 Application Steps

To apply for this Senior UX Designer position:

• Submit your application through the Thomson Reuters careers portal via the provided link.

• Tailor your resume: Highlight your 6+ years of experience, specific projects involving AI/LLM technologies, and skills in prompt design, user research, and complex workflow design. Use keywords from the job description.

• Curate your portfolio: Select 3-4 strong case studies that showcase your end-to-end design process, especially those demonstrating AI/LLM experience, systems thinking, and impactful outcomes. Prepare to present these clearly and concisely.

• Research Thomson Reuters: Understand their products, target users (professionals in legal, tax, etc.), and company values to articulate how your design philosophy aligns with their mission.

• Prepare for AI-specific questions: Be ready to discuss your experience designing for AI, building user trust, and navigating the complexities of generative AI and LLMs. Practice articulating your thought process for hypothetical AI design challenges.

⚠️ 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.