Senior UX Researcher – AI

Red Hat

. AI research tooling development .

Posted 5/1/2026full-timeRaleigh • North Carolina • 🇺🇸 United StatesSenior💰 $118,600 - $195,680 per yearWebsite

Tech Stack

Tools & technologies

PythonSDLCSQL

About the role

Key responsibilities & impact

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)
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.
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.
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.

Requirements

What you’ll need

5+ years conducting mixed-methods UX research (qualitative and quantitative) in an enterprise product development environment.
Bachelor's 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.

Benefits

Comp & perks

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!

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Hard Skills & Tools

AI research tooling developmentmixed-methods UX researchstatistical analysissurvey designdata analysisSQLRPythonAI/LLM-based toolsdata quality standards

Soft Skills

adaptabilityproblem-solvingattention to detailcommunicationcritical thinkingproject navigationcollaborationinsight generationmethodological rigorethics in research