Senior UX Researcher, Handshake Al

📍 Job Overview

Job Title: Senior UX Researcher, Handshake AI

Company: Handshake

Location: San Francisco, California, United States

Job Type: Full-Time

Category: Product & Design Operations / User Experience Research

Date Posted: March 1, 2026

Experience Level: Mid-Senior to Senior Level (based on title and responsibilities)

Remote Status: On-site (San Francisco)

🚀 Role Summary

• Lead comprehensive end-to-end UX research initiatives for Handshake AI's human data products, focusing on critical areas such as expert onboarding, annotation workflows, and internal operations systems that drive AI model development.

• Drive continuous improvement by meticulously tracking and measuring user sentiment, usability, and efficiency across complex platforms, translating findings into actionable product enhancements and operational efficiencies.

• Synthesize insights from both qualitative research methodologies and quantitative product analytics to inform strategic design decisions, product roadmaps, and the overall user experience for human data generators.

• Champion user-centered practices and advocate for user needs across cross-functional teams, including product, engineering, design, and operations, fostering a data-driven culture that prioritizes user experience and operational excellence within the AI economy.

📝 Enhancement Note: This role is positioned within the "AI economy" and focuses on "human data products" for LLM development. This implies a strong emphasis on understanding complex workflows, data quality, and operational efficiency in a cutting-edge technology space. The "Senior" title and responsibilities suggest a need for leadership in research strategy, stakeholder management, and influencing product direction, aligning it with advanced operations and product development functions.

📈 Primary Responsibilities

• Spearhead the planning, execution, and delivery of both evaluative and generative research studies throughout the entire product lifecycle, from initial concept exploration to the refinement of live tools and systems.

• Extract, analyze, and synthesize qualitative research findings and quantitative product analytics to construct compelling user stories, identify pain points, and uncover opportunities for product improvement and operational optimization.

• Develop and maintain a centralized repository of research insights, recommendations, and best practices to ensure institutional knowledge and facilitate data-informed decision-making across the organization.

• Recruit research participants independently, manage all logistical aspects of research studies with minimal overhead, and ensure ethical research practices are maintained.

• Deliver rapid, actionable insights that directly influence product improvements, enhance user experience, elevate product quality, and boost operational throughput and business impact, aligning research outcomes with key OKRs.

• Cultivate and maintain deep partnerships with cross-functional stakeholders, including product managers, designers, engineers, and operations teams, to ensure research initiatives are strategically aligned with business goals and product roadmaps.

• Champion the adoption of evidence-based, user-centered design and research practices across all product development teams, fostering a culture of continuous learning and user advocacy.

• Prioritize research initiatives in collaboration with design operations and design leadership, ensuring alignment with strategic objectives and resource allocation for maximum impact.

• Conduct research that directly improves services delivered to external users and optimizes internal operational workflows, demonstrating a clear link between research activities and tangible business outcomes.

• Track and measure how research findings influence key performance indicators such as OKRs, user engagement, task completion quality, throughput, and overall business impact, providing quantitative evidence of research value.

📝 Enhancement Note: The responsibilities highlight a dual focus on user experience for external experts and internal operational efficiency. This suggests the candidate will be involved in optimizing not just the user-facing platforms but also the backend systems that manage data generation and processing, a key aspect of GTM and operational effectiveness in AI development.

🎓 Skills & Qualifications

Education:

Experience:

• 5-10 years of progressive experience in UX research, with a significant portion focused on complex, high-impact platforms, including consumer-facing applications and internal operations tools.

• Proven track record of leading end-to-end research projects that have demonstrably influenced product strategy and delivered measurable business impact.

Required Skills:

• UX Research Expertise: Deep understanding and practical application of both qualitative (e.g., user interviews, ethnography, usability testing) and quantitative (e.g., surveys, analytics, A/B testing) research methods.

• AI Systems & LLM Workflows: Strong comprehension of AI systems, particularly Large Language Model (LLM) development workflows, and the critical role of human-in-the-loop (HITL) data in training and evaluation.

• Product Analytics & Data Synthesis: Ability to effectively synthesize qualitative research findings with quantitative product analytics and other data sources to form comprehensive user insights and compelling narratives.

• Lean Research Methods: Proficiency in applying lean research techniques to deliver actionable insights rapidly, often within days rather than weeks, to accelerate product development cycles.

• Cross-functional Collaboration: Demonstrated ability to build strong, collaborative partnerships with product management, engineering, design, operations, and other stakeholders to drive alignment and influence product direction.

• User-Centered Practices: Proven experience in championing and embedding user-centered design principles and research best practices within product development teams.

• Insight Delivery: Skill in producing clear, timely, and actionable research deliverables that directly inform product decisions and improve user and operational outcomes.

Preferred Skills:

• Experience with internal operations tools and systems, understanding the unique research needs and challenges associated with them.

• Knowledge of annotation platforms, data labeling processes, and the operational infrastructure supporting AI model training.

• Familiarity with design operations (DesignOps) principles and practices for streamlining research and design workflows.

• Experience informing content strategy, user flows, and workflow design through research findings.

• Ability to manage research participant recruitment and logistics independently with minimal supervision.

📝 Enhancement Note: The "5-10 years" experience level is inferred from the "Senior" title and the expectation of leading "end-to-end" research and influencing strategy, which typically requires substantial experience. The emphasis on AI and LLM workflows is a direct translation of the job description's core focus.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Case Studies: Showcase 2-3 detailed case studies demonstrating end-to-end UX research projects. Each case study should clearly outline the research problem, methodology employed, your specific role and contributions, key findings, and the impact of your research on product decisions and business outcomes.

• Methodology Diversity: Highlight experience with a range of research methodologies, including generative (e.g., exploratory research, concept testing) and evaluative (e.g., usability testing, A/B testing analysis) techniques, tailored to different stages of the product development lifecycle.

• Data Synthesis Examples: Include examples of how you've synthesized both qualitative and quantitative data (e.g., user interviews, surveys, product analytics, operational metrics) to derive actionable insights and inform strategy.

• Impact Demonstration: Clearly articulate the measurable impact of your research. Quantify improvements in user satisfaction, task completion rates, operational efficiency, product adoption, or business metrics where possible.

Process Documentation:

• Workflow Optimization: Present examples of how your research has identified inefficiencies or pain points in user workflows (e.g., expert annotation processes, onboarding flows) and how you've recommended or contributed to solutions that streamline these processes.

• System Improvement: Showcase instances where your research informed the design or improvement of complex platforms or internal operations systems, focusing on usability, clarity, and efficiency gains.

• Cross-functional Alignment: Demonstrate how you've documented and communicated research findings to diverse stakeholders (product, engineering, design, operations) to ensure alignment and drive consensus on product direction.

📝 Enhancement Note: For a Senior UX Researcher role, especially one focused on complex platforms and internal operations, a robust portfolio demonstrating end-to-end research leadership and impact is critical. The emphasis on "human data products" and "AI economy" necessitates showcasing research that directly impacts the efficiency and quality of data generation for AI models.

💵 Compensation & Benefits

Salary Range: $175,000 - $220,000 USD per year

Benefits:

• Ownership: Equity in a fast-growing company, providing a stake in Handshake's success.

• Financial Wellness: Comprehensive package including 401(k) with matching contributions, competitive base compensation, and access to financial coaching.

• Family Support: Generous paid parental leave, fertility benefits, and parental coaching to support employees and their families.

• Wellbeing: Robust health coverage (medical, dental, vision), dedicated mental health support, and a $500 annual wellness stipend.

• Growth & Development: A $2,000 annual learning stipend for professional development, ongoing training opportunities, and skill enhancement.

• Work Flexibility & Support: Internet and commuting stipends, with additional perks like free lunch and gym access at the San Francisco office.

• Time Off: Flexible Paid Time Off (PTO) policy, complemented by 15 company holidays and 2 additional flex days.

• Connection & Community: Opportunities for team outings and referral bonuses to foster a strong company culture.

Working Hours: 40 hours per week (standard full-time)

• While standard hours are 40 per week, the flexible PTO and emphasis on lean research methods suggest an environment that values efficient work and personal time, allowing for focused work periods and flexibility where possible.

📝 Enhancement Note: The salary range is directly provided in the input data. The benefits listed are also directly extracted and categorized for clarity, highlighting aspects particularly valuable to operations and product professionals, such as learning stipends and equity. The working hours are specified as 40, common for full-time roles.

🎯 Team & Company Context

🏢 Company Culture

Industry: Technology / AI / EdTech / Future of Work

Company Size: The description mentions "every foundational Al lab trust Handshake," "1 million employers (including 100% of the Fortune 50)," and "20 million knowledge workers," indicating a large and impactful platform. While precise employee count isn't given, the scale of operations and growth ("tripled our ARR at scale") suggests a medium to large, rapidly scaling tech company.

Founded: The company was founded in 2013 (information from company website). This indicates a company with established roots but also a dynamic, growth-oriented mindset, especially with its expansion into the "AI economy."

Team Structure:

• Cross-functional Product Teams: The UX Researcher will work within agile product teams, collaborating closely with Product Managers, Engineers, and Designers. The role emphasizes building "deep partnerships with cross-functional stakeholders," implying a matrixed or collaborative structure.

• Design & Operations Integration: The role involves close collaboration with "design operations and design leadership," suggesting a dedicated function that supports and streamlines design and research processes.

• Leadership Influence: The research findings are expected to influence "leadership," indicating that insights are shared and considered at higher organizational levels, particularly concerning strategic product direction and the "AI economy" focus.

Methodology:

• Evidence-Based & User-Centered: The core methodology is driven by user research, data analysis, and a commitment to user-centered practices, aiming to ground decisions in user needs and validated insights.

• Lean & Iterative: The emphasis on "lean research methods" and delivering "rapid, actionable insights" points to an iterative development process where research is integrated continuously to inform quick adjustments and improvements.

• Data-Driven Decision Making: Insights from both qualitative research and quantitative product analytics are critical for informing strategy, product development, and operational improvements.

Company Website: https://joinhandshake.com/

📝 Enhancement Note: The company's focus on the "AI economy" and "human data products" positions it at the forefront of technological advancement. The culture is likely fast-paced, innovative, and data-driven, with a strong emphasis on collaboration and measurable impact, typical of successful scale-up tech companies. The "AI" component suggests a need for researchers who can understand complex technical concepts and user behaviors within that domain.

📈 Career & Growth Analysis

Operations Career Level: This is a Senior UX Researcher role, indicating a mid-to-senior level position. It requires independent leadership in research strategy, execution, and influence. The role is expected to contribute significantly to product strategy and operational improvements within the Handshake AI division.

Reporting Structure: The role reports to "design operations and design leadership." This suggests a structure where research is integrated into the broader design function, with direct collaboration with product and engineering teams. The emphasis on "championing evidence-based, user-centered practices" implies a leadership role in advocating for research within these cross-functional teams.

Operations Impact: The UX Researcher's impact is directly tied to the success of Handshake AI's "human data products." This means influencing the development of platforms that generate critical data for LLMs, thereby accelerating AI research and improving model performance. The role's insights will directly affect user experience, operational efficiency, and the quality of AI training data, ultimately contributing to Handshake's ARR growth and market leadership in the AI economy.

Growth Opportunities:

• Specialization in AI Research: Deepen expertise in UX research specifically for AI development, human-in-the-loop systems, and data generation platforms, becoming a subject matter expert.

• Leadership in Research Strategy: Take on greater responsibility for defining the research agenda and strategy for Handshake AI, potentially leading research initiatives for new product lines or strategic growth areas.

• Cross-functional Influence: Expand influence across product, engineering, and business operations, potentially mentoring junior researchers or contributing to the broader product development framework.

• Contribution to a Disruptive Field: Play a key role in shaping the future of AI and the "AI economy" through user insights, offering a unique career path with significant industry impact.

• Learning & Development: Utilize the $2,000 learning stipend for advanced training, conferences, or certifications relevant to AI, UX research, and product development.

📝 Enhancement Note: The "Senior" designation implies a need for strategic thinking and the ability to operate with a high degree of autonomy, influencing product direction beyond just providing research findings. The growth opportunities are framed around specialization in a high-demand field (AI research) and increased leadership within a rapidly scaling company.

🌐 Work Environment

Office Type: The role is based in San Francisco and offers "free lunch/gym in our SF office," indicating a physical office presence is expected. This suggests a hybrid or primarily on-site work environment designed to foster collaboration.

Office Location(s): San Francisco, California, United States.

Workspace Context:

• Collaborative Hub: The San Francisco office likely provides a dynamic workspace designed for collaboration, with meeting rooms, breakout areas, and potentially open-plan seating to facilitate interaction among product, design, engineering, and operations teams.

• Access to Tools: As an on-site role in a tech company, expect access to modern technology, robust internet connectivity, and the necessary tools for UX research and collaboration.

• Team Interaction: The on-site nature facilitates spontaneous interactions, team brainstorming sessions, and direct engagement with colleagues, which is crucial for research that informs complex product development.

Work Schedule: The role is full-time, with a standard 40-hour work week. While the office environment supports collaboration, the emphasis on "lean research methods" and "flexible PTO" suggests a culture that respects individual work styles and encourages efficient, focused work periods.

📝 Enhancement Note: The explicit mention of office perks like free lunch and gym access, combined with the on-site requirement, strongly indicates a preference for in-person collaboration. This is common for roles that require close interaction with cross-functional teams, especially in fast-paced environments like AI development.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A recruiter or hiring manager will review your application and resume, focusing on alignment with the core requirements, particularly AI/LLM understanding and UX research experience.

• Hiring Manager Interview: A discussion focused on your experience, research philosophy, approach to complex problem-solving, and fit with the team and company culture. Be prepared to elaborate on your understanding of AI and human data.

• Portfolio Review & Presentation: You will likely present 1-2 key case studies from your portfolio to a panel of stakeholders (e.g., Design Lead, Product Manager, Engineering Lead). This is where you demonstrate your research process, insights, and impact.

• Cross-functional Interviews: Interviews with potential collaborators (e.g., Product Managers, Engineers) to assess your ability to work effectively in a cross-functional team, communicate research effectively, and integrate insights into product development.

• Final Round: May involve a discussion with senior leadership or a final assessment of strategic thinking and cultural fit.

Portfolio Review Tips:

• Tailor Your Portfolio: Select case studies that best highlight your experience with complex platforms, AI/LLM contexts, and driving operational efficiencies.

• Structure Your Narrative: For each case study, clearly articulate the "What" (problem), "Why" (business/user need), "How" (your research process), "So What" (key insights), and "Now What" (impact/recommendations).

• Quantify Impact: Whenever possible, use metrics to demonstrate the tangible outcomes of your research (e.g., % improvement in task completion, reduction in errors, increase in user satisfaction scores).

• Showcase Collaboration: Highlight how you partnered with product, design, and engineering teams, and how your research influenced their work.

• Prepare for Questions: Be ready to answer in-depth questions about your methodology, decision-making process, and how you handle challenging research scenarios or conflicting stakeholder needs.

Challenge Preparation:

• AI/LLM Context: Brush up on current trends in AI development, LLM training, and the role of human input (HITL). Understand common challenges in this space.

• Lean Research Scenarios: Be prepared to discuss how you would approach research under tight deadlines for a new AI feature or workflow.

• Operational Efficiency: Think about how UX research can directly impact operational metrics and efficiency in a data generation context.

• Stakeholder Management: Consider how you would communicate complex research findings to technical and non-technical stakeholders to gain buy-in and drive action.

📝 Enhancement Note: A portfolio review is standard for UX roles, and for a senior position in AI, it needs to demonstrate not just research skills but strategic thinking and impact. The emphasis on AI and operational efficiency requires candidates to showcase specific relevant projects.

🛠 Tools & Technology Stack

Primary Tools:

• UX Research Platforms: Familiarity with tools for user interviews, usability testing, and participant recruitment (e.g., UserTesting.com, Lookback, Maze, Dovetail).

• Survey Tools: Proficiency in creating and distributing surveys for quantitative data collection (e.g., SurveyMonkey, Typeform, Google Forms).

• Analytics Platforms: Experience with product analytics tools to understand user behavior and performance metrics (e.g., Amplitude, Google Analytics, Mixpanel).

• Data Visualization Tools: Ability to create clear visualizations of research findings and analytics data (e.g., Tableau, Power BI, Looker Studio).

Analytics & Reporting:

• Product Analytics Software: Tools like Amplitude or Mixpanel for tracking user engagement, feature adoption, and conversion funnels within the human data platforms.

• Reporting Dashboards: Experience creating and interpreting dashboards that track key user sentiment, usability, and efficiency metrics.

CRM & Automation:

• While not directly a CRM role, understanding how user data is managed and how processes are automated within internal operations systems is crucial. Familiarity with workflow automation tools or concepts might be beneficial.

📝 Enhancement Note: While specific tools aren't listed, the role's responsibilities point to a need for proficiency in common UX research and product analytics tools. The "internal operations systems" aspect suggests a need to be adaptable to various internal software and potentially understand how research integrates with automation processes.

👥 Team Culture & Values

Operations Values:

• User-Centricity: A deep commitment to understanding and serving the needs of human data experts and AI developers.

• Data-Driven Innovation: Utilizing research and analytics to drive informed decisions and foster continuous improvement in AI development processes.

• Collaboration & Partnership: Working hand-in-hand with cross-functional teams to achieve shared goals and build impactful products.

• Efficiency & Impact: Focusing on delivering rapid, actionable insights that lead to measurable improvements in product quality and operational performance.

• Adaptability & Learning: Embracing new technologies and methodologies in the fast-evolving AI landscape.

Collaboration Style:

• Proactive & Integrated: The role requires proactive engagement with product, engineering, and design to integrate research seamlessly into the development cycle.

• Evidence-Based Advocacy: Championing user needs and research findings through clear communication and data, influencing decisions across teams.

• Iterative Feedback Loops: Fostering a culture where feedback is regularly exchanged, and research findings are used for continuous iteration and improvement of both products and processes.

• Knowledge Sharing: Actively contributing to a centralized repository of insights and promoting the adoption of best practices across the organization.

📝 Enhancement Note: The company's values, as inferred from the description, emphasize innovation, collaboration, and a data-driven approach. For a Senior UX Researcher, this means being able to articulate user needs effectively, support product and operational strategies with concrete evidence, and work seamlessly within a fast-paced, cross-functional environment.

⚡ Challenges & Growth Opportunities

Challenges:

• Navigating Complex AI Workflows: Understanding and researching intricate human-in-the-loop processes for AI model training requires a steep learning curve and the ability to abstract complex technical concepts into user-centered problems.

• Balancing Speed and Rigor: The demand for "rapid, actionable insights" in a fast-paced AI development environment requires balancing the need for thorough research with the pressure for quick turnaround times.

• Influencing Technical Stakeholders: Effectively communicating user needs and research findings to highly technical teams (AI researchers, engineers) to drive adoption and product changes requires strong communication and persuasion skills.

• Measuring Impact in a New Field: Quantifying the direct impact of UX research on the performance of AI models and the efficiency of data generation can be challenging, requiring creative approaches to metric definition and tracking.

Learning & Development Opportunities:

• AI Research Specialization: Opportunity to become a leading UX researcher in the rapidly growing field of AI and human-data interaction.

• Strategic Product Influence: Develop skills in shaping product strategy and roadmaps through impactful research, contributing to high-stakes business decisions.

• Mentorship & Leadership: Potential to mentor junior researchers and contribute to the growth and development of the design and research function within Handshake AI.

• Industry Exposure: Engage with cutting-edge AI labs and educational institutions, staying at the forefront of AI development and career network innovation.

• Professional Development Budget: Leverage the $2,000 learning stipend for conferences, courses, or certifications relevant to AI, UX research, or product management.

📝 Enhancement Note: This section addresses the inherent difficulties of working in a novel and complex field like AI data products and highlights how overcoming these challenges leads to significant professional growth and specialization.

💡 Interview Preparation

Strategy Questions:

• AI & Human Data: "Describe your understanding of LLM development workflows and the role of human-in-the-loop data. How would you approach researching the effectiveness of an expert annotation tool?"

  • Preparation: Research common LLM training pipelines, data annotation types, and challenges. Frame your answer around understanding user workflows, identifying bottlenecks, and measuring data quality and efficiency.

• Research Leadership: "Tell me about a time you led an end-to-end UX research project for a complex platform. What was the outcome, and how did your research influence the product's direction or operational efficiency?"

  • Preparation: Prepare a STAR method (Situation, Task, Action, Result) answer focusing on a project that demonstrates your ability to manage research independently, synthesize complex data, and drive tangible impact.

• Lean Research & Impact: "How do you balance the need for rigorous research with the demand for rapid insights in a fast-paced environment? Provide an example where your lean research approach led to significant product improvements."

  • Preparation: Discuss methodologies like guerrilla testing, rapid prototyping feedback, or focused usability studies. Emphasize how you prioritize research questions to deliver value quickly without sacrificing essential validity.

Company & Culture Questions:

• Handshake AI Mission: "What excites you about Handshake's mission in the AI economy, and how do you see UX research contributing to that mission?"

  • Preparation: Research Handshake's platform, its impact on universities and employers, and its expansion into AI. Connect your passion for user-centered design to the company's goals.

• Cross-functional Collaboration: "Describe your experience working with product managers, engineers, and designers. How do you ensure your research insights are understood and acted upon by different disciplines?"

  • Preparation: Provide examples of how you tailor your communication, build relationships, and integrate research findings into team processes.

Portfolio Presentation Strategy:

• Focus on Impact: For each case study, clearly articulate the business problem, your research objectives, key findings, and the quantifiable impact of your recommendations.

• Showcase Process: Walk through your methodology, explaining why you chose certain methods and how they addressed the research questions.

• Highlight Collaboration: Explain how you partnered with stakeholders throughout the research process.

• Be Ready for Deep Dives: Anticipate detailed questions about your methods, data analysis, and decision-making rationale.

📝 Enhancement Note: Interview preparation for a Senior UX Researcher in AI requires demonstrating not only research acumen but also strategic thinking, understanding of the AI domain, and strong communication skills to influence technical stakeholders.

📌 Application Steps

To apply for this Senior UX Researcher position:

• Submit your application through the provided link on Ashby.

• Portfolio Customization: Tailor your resume and portfolio to highlight your experience with AI/LLM workflows, complex platform research, and driving operational efficiencies. Ensure your case studies clearly demonstrate end-to-end research leadership and measurable impact.

• Resume Optimization: Use keywords from the job description such as "UX Research," "LLM development," "human-in-the-loop," "product analytics," "lean research," and "cross-functional collaboration" to ensure your resume is easily discoverable by Applicant Tracking Systems (ATS).

• Interview Preparation: Practice articulating your research process, insights, and impact using the STAR method. Prepare specific examples related to AI, complex systems, and operational improvements. Rehearse your portfolio presentation for clarity and conciseness.

• Company Research: Thoroughly research Handshake's mission, products, and recent news, particularly their expansion into AI. Understand their market position and how your role contributes to their growth and impact in the AI economy.

⚠️ 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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