Were looking for a Senior UX Researcher to join our UX Research Program and Practice team and work at the intersection of user research data science and AI-augmented research. This is not a traditional generalist research role. Youll split your time across four distinct workstreams: developing and evaluating AI-driven research tools analyzing participant data to strengthen recruitment quality building a structured machine-readable research repository and conducting mixed-methods research (including benchmarking and UX measurement).
What you will do:
AI research tooling development
Contribute to a shared repository of AI-driven UX research tools that augment and scale the research workflow.
Design evaluation rubrics for AI output quality assessing AI-generated research artifacts for things like accuracy tone bias and interpretive validity.
Iterate on tools based on measurable performance criteria balancing automation with methodological rigor.
Integrate research tooling into the software development lifecycle (SDLC)
Participant database and recruitment strategy
Query and analyze the existing participant database (SQL R or Python) to identify sampling biases demographic gaps and representation issues.
Develop data-driven recruitment strategies that address identified gaps.
Design and validate surveys and screening instruments to qualify participants.
Report findings accurately using statistical methods appropriate to the data types involved.
Structured research repository
Transform qualitative and quantitative research data into atomic structured units suitable for cross-system consumption.
Define and maintain the schema and taxonomy that make qualitative findings machine-readable and queryable.
Enable downstream systems (AI tools dashboards cross-functional workflows) to leverage research findings without manual retrieval.
Ensure data quality and consistency standards across the repository.
Mixed-methods research
Conduct research using existing data sources survey backlogs customer feedback repositories support tickets prior study findings to surface patterns and generate new insights.
Design and execute UX benchmarking studies using standardized instruments to establish baselines and measure change over time.
Pair qualitative findings with behavioral analytics or benchmark data to triangulate insights and strengthen evidence.
What you will bring:
5 years conducting mixed-methods UX research (qualitative and quantitative) in an enterprise product development environment.
Bachelors degree in a technical or human-centered field (e.g. HCI Data Science Information Systems Computer Science Psychology) or equivalent practical experience.
Demonstrated ability to navigate complex ambiguous projects and adapt methods in response to new information or changing conditions.
Experience developing evaluating and using AI/LLM-based tools in a research context and think carefully about reliability and failure modes.
Proficiency querying and analyzing large datasets using SQL R or Python.
Statistical analysis fluency ability to select and apply methods appropriate to the data type and report findings with confidence.
Survey and screener design with attention to sampling validity; proficient in Qualtrics.
Experience building or contributing to research repositories taxonomies or knowledge management systems
Strong understanding of research ethics particularly participant privacy data handling and bias mitigation
Experience with secondary analysis synthesizing findings across multiple existing studies surveys or feedback channels.
Following is considered a plus:
Comfort working in code repositories and collaborating with engineering teams (Git Markdown CLI tools)
Prompt engineering evaluation frameworks or AI output quality assessment experience.
Experience with frameworks like Jobs to Be Done mental models or similar approaches to structuring qualitative insights
Experience with UX metrics programs defining KPIs tracking longitudinal benchmarks reporting to stakeholders
Foundational understanding of RAG pipelines with vector stores chunking strategies and embedding models
Pay Transparency
Red Hat determines compensation based on several factors including but not limited to job location experience applicable skills and training external market value and internal pay equity. Annual salary is one component of Red Hats compensation package. This position may also be eligible for bonus commission and/or equity. For positions with Remote-US locations the actual salary range for the position may differ based on location but will be commensurate with job duties and relevant work experience.
About Red Hat
Benefits
Comprehensive medical dental and vision coverage
Flexible Spending Account - healthcare and dependent care
Health Savings Account - high deductible medical plan
Retirement 401(k) with employer match
Paid time off and holidays
Paid parental leave plans for all new parents
Leave benefits including disability paid family medical leave and paid military leave
Additional benefits including employee stock purchase plan family planning reimbursement tuition reimbursement transportation expense account employee assistance program and more!
Note: These benefits are only applicable to full time permanent associates at Red Hat located in the United States.
Inclusion at Red Hat
Red Hats culture is built on the open source principles of transparency collaboration and inclusion where the best ideas can come from anywhere and anyone. When this is realized it empowers people from different backgrounds perspectives and experiences to come together to share ideas challenge the status quo and drive innovation. Our aspiration is that everyone experiences this culture with equal opportunity and access and that all voices are not only heard but also celebrated. We hope you will join our celebration and we welcome and encourage applicants from all the beautiful dimensions that compose our global village.
Equal Opportunity Policy (EEO)
Red Hat is proud to be an equal opportunity workplace and an affirmative action employer. We review applications for employment without regard to their race color religion sex sexual orientation gender identity national origin ancestry citizenship age veteran status genetic information physical or mental disability medical condition marital status or any other basis prohibited by law.
Required Experience:
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