Sr. UX Designer

📍 Job Overview

Job Title: Sr. UX Designer

Company: Thomson Reuters

Location: Toronto, Ontario, Canada

Job Type: Full time

Category: Product Design / UX Design (with a focus on AI & Generative UX)

Date Posted: 2026-08-31

Experience Level: 6+ years professional experience

Remote Status: Hybrid

🚀 Role Summary

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

• Translate complex AI model behaviors, data inputs, and system constraints into intuitive, trustworthy, and high-impact user experiences.

• Collaborate closely with product management, product engineering, and data science to define user-AI collaboration patterns, transparency moments, and control surfaces.

• Leverage AI/LLM prototyping to evaluate user prompts, refine model responses, and inform strategic product direction, ensuring responsible AI practices are at the forefront of design.

📝 Enhancement Note: This role is positioned at the Senior level, indicating a need for significant autonomy, leadership in design initiatives, and the ability to influence product strategy. The emphasis on AI and LLM technologies signifies a specialized and forward-thinking UX design function within Thomson Reuters.

📈 Primary Responsibilities

• Lead the full product design lifecycle for AI-powered features, from ideation and concept development to detailed interaction design and final implementation support.

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

• Engage in hands-on prototyping with real AI/LLM models to evaluate user prompts, iteratively improve model responses, and provide critical feedback to inform product strategy and development.

• Map out and design sophisticated collaboration patterns between users and AI, clearly defining autonomous AI actions, human control points, and seamless handoff mechanisms.

• Create detailed interaction flows that incorporate essential transparency moments, robust safety guardrails, effective override options, and clear recovery states to ensure predictable user experiences.

• Partner with data science and engineering teams to shape AI model requirements, assess performance constraints, and ensure system behaviors are optimally aligned with user needs and business objectives.

• Collaborate with UX Research to conduct rigorous usability testing and specialized AI validation studies to understand user mental models, key trust factors, and nuanced interaction expectations.

• Utilize qualitative and quantitative data to conduct evaluative studies for AI features, focusing on metrics such as prompt/response quality, hallucination risk, and trust signals.

• Contribute to the development and maintenance of internal design standards for AI patterns, prompt design guidelines, AI feature evaluation criteria, and UX quality benchmarks.

• Partner with product and research teams to identify and explore new opportunities where AI can deliver significant improvements and value to users.

• Communicate design decisions with exceptional clarity, effectively influence senior stakeholders, and guide cross-functional teams through ambiguous or rapidly evolving problem spaces.

• Leverage AI tooling and internal content standards to deliver clear, concise, and brand-aligned product experiences that are both functional and aesthetically cohesive.

• Design accessible solutions and collaborate with the Accessibility team to ensure WCAG 2.1 AA compliance, integrating AI checks with expert review for comprehensive coverage.

📝 Enhancement Note: The responsibilities highlight a deep dive into AI-specific UX challenges, moving beyond traditional interface design to encompass the complexities of human-AI interaction, model behavior interpretation, and responsible AI integration. This role demands a blend of strategic thinking, technical understanding of AI, and strong design execution.

🎓 Skills & Qualifications

Education: While no specific degree is listed, a Bachelor's or Master's degree in Human-Computer Interaction (HCI), Design, Computer Science, or a related field is typically expected for a Senior UX Designer role.

Experience: 6+ years of professional product design experience with a proven track record of end-to-end ownership of complex, user-centered workflows.

Required Skills:

• AI/LLM Design Expertise: Demonstrated experience designing with AI or Large Language Model (LLM) technologies, including prompt design, generative UX, and evaluating model output quality.

• Interaction Design: Strong proficiency in creating intuitive and effective interaction designs, particularly in simplifying complex or ambiguous AI behaviors into predictable, user-centered experiences.

• Prototyping: Ability to create functional prototypes using industry-standard tools such as Figma, and potentially coding tools like Python notebooks or utilizing model sandboxes and no-code AI orchestration platforms.

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

• Systems Thinking: Deep systems-thinking skills with a comfort level in designing across multiple layers: User Interface (UI), data inputs, model constraints, and operational workflows.

• Cross-functional Collaboration: Proven experience collaborating effectively with product management, product engineering, data science, product analytics, user research, content design, accessibility, and UX engineering teams within high-velocity, cross-functional environments.

• Communication & Storytelling: Exceptional communication and storytelling skills, with the ability to clearly articulate design decisions, influence stakeholders, and explain the "why" behind design choices.

• Responsible AI Principles: A strong commitment to responsible AI principles, including transparency, fairness, accountability, and user empowerment in design.

• Growth Mindset & Ambiguity Navigation: A proactive growth mindset, comfort with navigating ambiguity, and enthusiasm for experimenting with emerging technologies.

Preferred Skills:

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

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

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

• Domain Expertise: Familiarity with domain-heavy environments such as legal research, tax and compliance, risk and fraud, or financial analysis, and the ability to translate complexity into usable experiences.

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

📝 Enhancement Note: The emphasis on AI/LLM experience, prompt design, and model behavior familiarity is critical. Candidates should be prepared to showcase how they've navigated the unique challenges of designing for AI, including uncertainty, trust, and explainability, in their portfolios. The "Bonus" skills are significant differentiators, particularly domain expertise for Thomson Reuters' core markets.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• End-to-End Ownership: Showcase at least 2-3 complex projects demonstrating end-to-end UX design ownership, from initial problem definition and user research to final design and post-launch iteration.

• AI/LLM Focus: Highlight specific examples of designing with AI or LLM technologies. This could include prompt engineering, generative UX, designing for model feedback loops, or addressing issues like hallucination and trust.

• Problem-Solving & Process: Clearly articulate the design process used for each project, emphasizing how user needs, business goals, and technical constraints (especially AI model behaviors) were balanced.

• Impact & Metrics: Quantify the impact of your designs whenever possible, using metrics related to user engagement, task completion, efficiency gains, user satisfaction, and, importantly for this role, trust and adoption of AI features.

• Prototyping & Tools: Include examples of your prototyping work, detailing the tools used (Figma, Python notebooks, etc.) and how prototypes were leveraged to test hypotheses or gather feedback on AI interactions.

Process Documentation:

• Workflow Design & Optimization: Demonstrate the ability to map complex user journeys and workflows, particularly those involving human-AI collaboration, and showcase how these were optimized for clarity, efficiency, and trust.

• Implementation & Automation: Provide examples of how designs were translated into actionable specifications for engineering and data science teams, and how automation principles were applied to enhance user experience.

• Measurement & Analysis: Show evidence of how you used qualitative (e.g., usability testing, interviews) and quantitative data (e.g., analytics, AI evaluation metrics) to measure the success of your designs and inform iterative improvements.

📝 Enhancement Note: For this role, a portfolio is not just a collection of past work but a demonstration of a candidate's ability to think critically about complex, emerging technologies like AI. Candidates should be prepared to walk through their decision-making process for AI-specific design challenges, including how they addressed ambiguity and ensured responsible AI development.

💵 Compensation & Benefits

Salary Range: For Ontario, Canada, the base compensation range for this role is $105,000 CAD - $155,000 CAD per year.

Explanation: This range is based on the provided information for Thomson Reuters in Ontario, Canada. It reflects the Senior level experience required (6+ years), the specialized nature of AI/LLM UX design, and the competitive market for such talent in a major city like Toronto. The exact placement within the range will depend on the candidate's specific skills, experience, and alignment with the role's requirements.

Benefits:

• Hybrid Work Model: Offers flexibility for in-office collaboration and remote work.

• Flexibility & Work-Life Balance: Includes "Flex My Way" policies, allowing for management of personal and professional responsibilities, and up to 8 weeks per year of "work from anywhere."

• Career Development & Growth: Access to "Grow My Way" programming, skills-first approach, and continuous learning opportunities to prepare for an AI-enabled future.

• Industry Competitive Benefits: Comprehensive plans including flexible vacation, two company-wide Mental Health Days off, Headspace app access, retirement savings, tuition reimbursement, employee incentive programs, and resources for mental, physical, and financial wellbeing.

• Social Impact: Two paid volunteer days off annually, with opportunities for pro-bono consulting and ESG initiatives.

Working Hours: The standard working hours are not explicitly stated but are typically around 40 hours per week for a full-time role. The hybrid model and "Flex My Way" policies suggest a degree of flexibility in scheduling.

📝 Enhancement Note: The salary range is explicitly provided. The benefits package is robust, emphasizing work-life balance, professional development, and employee wellbeing, which are attractive aspects for experienced professionals in the tech and design fields. The "work from anywhere" policy is a significant perk.

🎯 Team & Company Context

🏢 Company Culture

Industry: Information Services, Technology, and Media. Thomson Reuters is a global leader in providing trusted content and technology solutions for professionals in legal, tax, accounting, compliance, government, and media.

Company Size: Large enterprise (over 26,000 employees globally). This size suggests established processes, significant resources, and opportunities for large-scale impact, but also the potential for navigating complex organizational structures.

Founded: Thomson Reuters has a long history, formed from the merger of Thomson Corporation and Reuters Group in 2008, with roots tracing back much further. This history implies stability, deep industry knowledge, and a strong established presence.

Team Structure:

• AI Product Design Team: This role is part of a specialized UX design function focused on AI, likely working within or closely alongside product management, product engineering, and data science teams. The team is expected to be cross-functional and agile.

• Reporting Structure: While not explicitly detailed, a Senior UX Designer typically reports to a UX Lead, Design Manager, or Director of Product Design. They are expected to work autonomously on their assigned features and collaborate broadly.

• Cross-functional Collaboration: The role emphasizes close partnerships with Product Management (strategy, requirements), Product Engineering (implementation), Data Science (model behavior, constraints), UX Research (validation, insights), Content Design (messaging, tone), Accessibility, and UX Engineering.

Methodology:

• Data-Driven Insights: The company values using qualitative and quantitative data to inform design decisions, including AI-specific evaluation metrics and user research.

• Agile & Iterative: The description mentions "high-velocity, cross-functional teams" and "iterating rapidly," suggesting an agile development environment where design is integrated throughout the product lifecycle.

• Responsible AI Focus: A core methodological principle is commitment to responsible AI, ensuring fairness, transparency, and user empowerment in all AI-driven designs.

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

📝 Enhancement Note: Thomson Reuters operates in critical professional sectors where accuracy, trust, and transparency are paramount. This context is crucial for understanding the emphasis on responsible AI and designing for complex, knowledge-intensive domains. The company's global scale means impact can be far-reaching.

📈 Career & Growth Analysis

Operations Career Level: This is a Senior-level Product/UX Designer role. It signifies a move beyond individual contribution to include design leadership, mentorship potential, and significant influence on product strategy and design direction, particularly within the emerging field of AI product design.

Reporting Structure: The Senior UX Designer will likely report to a Design Manager or Director, working within a product team that includes Product Managers, Engineers, and Data Scientists. They are expected to lead design efforts for specific AI features and collaborate broadly across departments.

Operations Impact: The role has a direct impact on the usability, trustworthiness, and adoption of Thomson Reuters' AI-powered products. Successful UX design for AI can significantly enhance user productivity, decision-making accuracy, and overall customer satisfaction, thereby driving revenue and competitive advantage.

Growth Opportunities:

• Specialization in AI UX: Deepen expertise in designing for cutting-edge AI/LLM technologies, becoming a go-to expert within the company and potentially the industry.

• Leadership & Mentorship: Take on leadership responsibilities for design initiatives, mentor junior designers, and contribute to evolving design standards and best practices for AI.

• Cross-functional Influence: Expand influence across product strategy, R&D, and business units by demonstrating the value of user-centered AI design.

• Product Strategy Contribution: Contribute to defining the future roadmap of AI-powered products, identifying new opportunities and user needs that AI can address.

• Advancement: Potential career progression to Lead UX Designer, Design Manager, or Principal UX Designer roles, focusing on either deeper specialization or broader team leadership.

📝 Enhancement Note: The role offers a significant opportunity to be at the forefront of AI product design within a large, established company. Growth is likely tied to developing specialized AI UX skills and demonstrating leadership in navigating complex, ambiguous design challenges.

🌐 Work Environment

Office Type: Hybrid work model, blending in-office collaboration with remote flexibility. This suggests a modern office environment designed for collaboration, team meetings, and focused individual work.

Office Location(s): Toronto, Ontario, Canada. Specific office address details are not provided but are likely accessible through the company's careers portal or upon interview.

Workspace Context:

• Collaborative Environment: The hybrid model implies spaces conducive to team syncs, brainstorming sessions, and cross-functional alignment.

• Tools & Technology: Access to industry-standard design tools (Figma), AI/LLM prototyping environments, and potentially internal development tools and platforms.

• Team Interaction: Opportunities for regular interaction with UX designers, researchers, product managers, engineers, and data scientists, both in person and virtually.

Work Schedule: Full-time, with stated flexibility through "Flex My Way" policies and "work from anywhere" options. This allows for a balance between structured workdays and personal needs, particularly beneficial for deep-focus design tasks.

📝 Enhancement Note: The emphasis on a hybrid model and "Flex My Way" indicates a company culture that values employee autonomy and work-life balance, which is a significant draw for experienced professionals. The workspace is expected to support both individual deep work and dynamic team collaboration.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: HR or Recruiter screen to assess basic qualifications, experience, and cultural fit.

• Portfolio Review & Design Challenge: A deep dive into the candidate's portfolio, focusing on AI/LLM design examples. This may be followed by a design challenge (take-home or live) to assess problem-solving skills, process, and ability to articulate design decisions under pressure.

• Hiring Manager Interview: Discussion with the hiring manager to assess strategic thinking, leadership potential, and alignment with team goals.

• Cross-functional Interviews: Interviews with key collaborators (e.g., Product Manager, Engineering Lead, Data Scientist) to evaluate teamwork, communication, and ability to influence across disciplines.

• Final Round/Executive Interview: Potentially a final interview with a senior leader to confirm overall fit and strategic alignment.

Portfolio Review Tips:

• Curate for AI: Select projects that best showcase your experience with AI/LLM, prompt design, generative UX, and responsible AI principles. Clearly explain the problem, your process, your specific contributions, and the outcomes.

• Tell a Story: Structure your case studies to tell a compelling narrative. Emphasize the "why" behind your decisions, the challenges you faced (especially AI-related ones), and how you overcame them.

• Demonstrate Impact: Quantify results whenever possible. For AI projects, focus on metrics related to user trust, adoption, efficiency gains, and response quality.

• Showcase Process: Detail your design process, including research methods, ideation techniques, prototyping tools, and how you collaborated with technical teams (engineering, data science).

• Be Ready for Questions: Anticipate questions about your approach to ambiguous problems, how you handle technical constraints of AI models, and your understanding of responsible AI.

Challenge Preparation:

• Understand the Context: If given a take-home challenge, thoroughly research Thomson Reuters' products and their potential applications of AI.

• Focus on Process: Demonstrate a clear, logical design process. Articulate your assumptions and how you would validate them.

• AI-Specific Considerations: For any AI-related challenge, address aspects like prompt design, user feedback loops, transparency, and potential ethical considerations.

• Presentation Skills: Be prepared to present your work concisely and persuasively, highlighting key decisions and outcomes. Practice explaining complex ideas simply.

📝 Enhancement Note: The interview process is likely to be rigorous, with a strong emphasis on portfolio quality and the ability to articulate complex design decisions related to AI. Candidates should prepare specific examples that highlight their unique skills in this emerging field.

🛠 Tools & Technology Stack

Primary Tools:

• Prototyping & Design: Figma is explicitly mentioned. Adobe Creative Suite (Illustrator,

Photoshop) may also be used for asset creation.

• AI/LLM Prototyping: This is a key differentiator. Expect requirements for using or understanding:

  • Python Notebooks: For scripting, data analysis, and potentially direct interaction with models.
  • Model Sandboxes: Environments for experimenting with AI models.
  • No-code AI Orchestration Tools: Platforms that allow for building and testing AI workflows without extensive coding.

• Collaboration Tools: Standard tools like Slack, Microsoft Teams, Jira, Confluence, etc., for team communication and project management.

Analytics & Reporting:

• Product Analytics Tools: Experience with tools like Google Analytics, Adobe Analytics, Amplitude, or similar platforms to track user behavior and feature adoption.

• Data Visualization Tools: Proficiency in tools like Tableau, Power BI, or even advanced Figma features for creating dashboards and reports to communicate insights.

• AI Evaluation Metrics: Familiarity with metrics specific to AI performance (e.g., accuracy, precision, recall, F1-score for classification; BLEU, ROUGE for generation; user satisfaction scores related to AI output).

CRM & Automation:

• CRM Systems: Experience with CRM platforms like Salesforce is often beneficial for understanding sales and customer data flows, though not explicitly listed.

• Workflow Automation: Understanding of how design can integrate with and leverage automation tools to streamline user tasks and operational processes.

• Integration Tools: Awareness of how different systems (e.g., AI models, front-end applications, databases) connect and exchange data.

📝 Enhancement Note: The tech stack emphasizes modern design tools (Figma) and critically, hands-on experience with AI/LLM prototyping environments. This is not a passive role; active experimentation with AI models is expected. Proficiency in data analysis and understanding AI performance metrics is also crucial.

👥 Team Culture & Values

Operations Values:

• Customer Obsession: A strong focus on understanding and meeting the needs of Thomson Reuters' professional customers.

• Competition & Winning: A drive to excel and lead in the market through innovation and superior product offerings.

• Challenging Thinking: An encouragement of critical thinking, questioning the status quo, and seeking continuous improvement.

• Act Fast / Learn Fast: An agile approach to development and problem-solving, embracing experimentation and rapid iteration.

• Stronger Together: A value placed on collaboration, teamwork, and leveraging diverse perspectives.

• Responsible AI: A commitment to ethical development and deployment of AI, prioritizing transparency, fairness, and user empowerment.

Collaboration Style:

• Cross-functional Integration: Designers are expected to be integrated members of product teams, working seamlessly with engineering, product management, and data science.

• Data-Informed Decision Making: Collaboration is guided by data and user insights, fostering a culture where design decisions are backed by evidence.

• Open Communication & Feedback: An environment where ideas are shared openly, and constructive feedback is regularly exchanged to refine designs and processes.

• Experimentation & Learning: A culture that supports trying new approaches, especially with emerging technologies like AI, and learning from both successes and failures.

📝 Enhancement Note: The company values align well with the demands of designing for AI: a blend of competitive drive, rapid learning, and a strong ethical compass for responsible innovation. Collaboration is key, requiring designers to be effective communicators and team players across diverse technical and business functions.

⚡ Challenges & Growth Opportunities

Challenges:

• Navigating AI Ambiguity: Designing for AI, especially generative AI, involves inherent uncertainty. A key challenge will be translating probabilistic and sometimes unpredictable model behaviors into predictable and trustworthy user experiences.

• Building User Trust in AI: Educating users, ensuring transparency, and designing robust feedback mechanisms will be critical to fostering trust in AI-powered features, especially in sensitive professional domains.

• Balancing Innovation with Responsibility: Innovating with AI while adhering to responsible AI principles (fairness, transparency, safety) requires careful design considerations and cross-functional alignment.

• Integrating AI into Existing Workflows: Seamlessly embedding new AI capabilities into established professional workflows without causing disruption or adding cognitive load.

• Rapid Technological Evolution: Keeping pace with the rapid advancements in AI technology and adapting design approaches accordingly.

Learning & Development Opportunities:

• AI UX Specialization: Becoming a leader in the rapidly growing field of AI and Generative UX design, developing highly sought-after skills.

• Cross-Disciplinary Learning: Gaining deep insights into data science, model behaviors, and product strategy through close collaboration.

• Industry Conferences & Training: Opportunities to attend AI and UX conferences, workshops, and pursue certifications to stay at the forefront of the field.

• Mentorship: Potential to be mentored by senior leaders or to mentor junior designers, developing leadership and coaching skills.

• Impactful Projects: Working on products that have a significant real-world impact, helping professionals in critical fields make better decisions.

📝 Enhancement Note: The challenges are directly tied to the cutting-edge nature of the role. Success will depend on adaptability, a strong problem-solving mindset, and a proactive approach to learning. The growth opportunities are substantial for those looking to specialize in AI UX.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you designed a complex workflow. How did you simplify it for users, and what was the outcome?" (Focus on process, problem-solving, and impact.)

• "How would you approach designing a feature where an AI model might sometimes 'hallucinate' or provide incorrect information?" (Assess understanding of AI limitations, trust, and mitigation strategies.)

• "Walk me through your process for designing an AI-powered feature from initial concept to launch. What were the key collaboration points with engineering and data science?" (Evaluate end-to-end process, collaboration skills, and AI integration.)

• "How do you ensure user trust when designing AI-driven experiences?" (Probe understanding of transparency, explainability, and user control.) Company & Culture Questions:

• "Based on your understanding of Thomson Reuters, where do you see the biggest opportunities for AI to enhance our professional products?" (Assess research, strategic thinking, and domain interest.)

• "How do you align your design work with company values like 'Customer Obsession' or 'Act Fast / Learn Fast'?" (Evaluate cultural fit and understanding of company ethos.)

• "Describe a situation where you had to influence senior stakeholders on a design decision. How did you approach it?" (Assess communication, persuasion, and leadership.) Portfolio Presentation Strategy:

• Structure Your Narrative: For each project, clearly define the problem, your role, the user needs, the business goals, your design process, the AI-specific challenges, your solutions, and the measurable impact.

• Highlight AI Expertise: Dedicate specific slides or talking points to your AI/LLM design experience. Show prototypes, explain prompt design choices, and discuss how you handled model constraints.

• Quantify Impact: Use data and metrics to demonstrate the success of your designs. If direct metrics are unavailable, use qualitative feedback or projected benefits.

• Be Ready for Deep Dives: Anticipate detailed questions about your design decisions, trade-offs, and the technical feasibility of your solutions.

• Showcase Collaboration: Explain how you worked with engineers, data scientists, and product managers, and how you incorporated their feedback.

📝 Enhancement Note: Interview preparation should heavily focus on articulating your experience with AI/LLM design and demonstrating how you apply user-centered principles to complex, emerging technologies. Be prepared to discuss the ethical considerations of AI and how you integrate responsible design practices.

📌 Application Steps

To apply for this Sr. UX Designer position:

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

• Curate Your Portfolio: Select 2-3 of your strongest projects that best showcase your end-to-end design process, with a particular emphasis on any AI/LLM or complex workflow design experience. Ensure each project clearly outlines the problem, your role, your process, your solutions, and the impact.

• Tailor Your Resume: Highlight keywords and experiences directly relevant to the job description, such as "UX design," "AI product design," "LLM technologies," "prompt design," "interaction design," "user research," "Figma," and "responsible AI." Quantify achievements where possible.

• Prepare Your Presentation: Practice walking through your portfolio projects concisely and persuasively. Be ready to articulate your design decisions, especially those related to AI, and answer detailed questions about your process and impact.

• Research Thomson Reuters: Understand the company's mission, its core professional markets (legal, tax, etc.), and how AI might be applied to enhance its offerings. Familiarize yourself with their stated values and culture.

⚠️ 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.