Program Manager I, Tech (QA Automation)

About the team

• We are the QA Tech Strategy & Automation team within Global Support Services (GSS) Quality Assurance. We make the quality of customer-support tools and experiences measurable, repeatable and AI-assisted.

• We own test automation across mobile (Android/iOS), web and backend systems for multiple lines of business, and we run it on Uber's in-house automation platform as part of CI/CD and release validation.

• We build and apply in-house GenAI solutions to quality engineering: AI-assisted test generation, self-healing tests, automated failure triage and risk-based test prioritization.

• We partner closely with Engineering, Product, Operations and regional QA teams to catch defects at the source and raise release confidence, and we measure it: test coverage, maintenance effort, defect leakage and release reliability.

• We are a collaborative, global team that favors experimentation: prototype quickly, measure accuracy and reliability, then scale what works.

What you'll do

• Own and drive GenAI-based quality engineering programs end to end, from problem definition and prototype through delivery and adoption.

• Build and deploy GenAI solutions (LLMs, agents and automation frameworks) for test generation, regression detection, failure analysis and coverage improvement.

• Integrate these solutions into engineering workflows and CI/CD pipelines so quality signals reach teams early and automatically.

• Turn complex quality problems into working prototypes, evaluate their accuracy and reliability, and work with engineering teams to scale the ones that succeed.

• Define and track metrics for defect detection, testing efficiency, test maintenance effort and release quality, and report progress to stakeholders and leadership.

• Work with Engineering, Product and QA leads to prioritize automation coverage, reduce defect leakage and strengthen release gating.

• Contribute to the team's strategy, roadmap and strategy-of-record, and spread best practices in AI-assisted quality across teams.

What you'll need

• 5+ years in quality engineering, test automation or technical program management, with hands-on ownership of quality initiatives for large-scale software systems.

• Demonstrated experience building and deploying GenAI solutions to quality engineering problems, such as test generation, regression detection, failure analysis and test coverage improvement.

• Proficiency in Python or a similar language, with experience integrating LLMs, agents and automation frameworks into engineering workflows and CI/CD pipelines.

• Ability to turn complex quality challenges into working prototypes, evaluate accuracy and reliability, and partner with engineering teams to scale them.

• Proven ability to drive cross-functional programs from problem definition through delivery, using metrics to show improvements in defect detection, testing efficiency and release quality.