Senior Staff SDET (Customer Engineering)

• The best SDETs in the industry are no longer measured by how many tests they write. They’re measured by the systems they build that decide whether software is safe to ship — and, increasingly, by how well they wield AI to do it
• That’s the role we’re hiring for. We’re looking for a Senior Staff SDET to own quality architecture and engineering strategy for our most critical systems, and to lead how we apply AI across our entire testing and release pipeline. You’ll build the frameworks, platforms, and agent-driven workflows that the rest of engineering depends on, define what “safe to ship” means here, and stay deep in the code while doing it
• This is a genuinely hands-on senior technical leadership role with impact that spans many teams. If you want to build AI-native quality systems rather than bolt AI tools onto a legacy suite, this is that job
• AI is the core of the work. You’ll own how we use LLMs and agents for test generation, failure triage, self-healing, and release decisioning — and you’ll set the guardrails that keep it trustworthy
• You’ll test AI, not just test with it. We ship AI-powered product features, which means building evaluation harnesses, golden datasets, and probabilistic assertions for systems that don’t return the same answer twice. This is frontier work with very little established playbook
• Real autonomy and real scope. You’ll set the technical direction for quality engineering, not inherit someone else’s strategy
• Own quality architecture for our most critical systems and initiatives, defining long-term quality strategy aligned with business and product goals
• Design shared quality platforms, automation frameworks, and test infrastructure that are adopted across multiple teams
• Establish quality patterns and guardrails that scale across teams, eliminating duplicated, brittle, or low-signal testing approaches through platform-level solutions
• Anticipate systemic quality and reliability risks and drive preventative architectural solutions before they impact customers
• Set the standard for what “great” looks like in quality engineering at scale
• Define and drive our strategy for AI-assisted testing — autonomous test generation, intelligent test selection, agent-based failure triage, and self-healing automation — with a clear-eyed view of where each genuinely pays off and where it adds noise
• Build the guardrails that make AI-driven testing trustworthy: knowing when a self-healing agent is masking a real regression versus absorbing harmless implementation drift is the difference between leverage and liability
• Orchestrate AI agents as part of the CI/CD decision pipeline, turning raw test signal into release confidence rather than more dashboards
• Own quality for our AI-powered product features — designing eval suites, golden datasets, LLM-as-judge scorers, and statistical approaches for non-deterministic behavior, plus testing for hallucination, safety, and response stability
• Establish how we test AI-generated application code, validating behavioral correctness and not just syntactic plausibility
• Evaluate emerging AI testing tooling with real rigor, and be honest about what doesn’t work
• Lead the operational maturity of our quality systems and signals — defining quality metrics, dashboards, and release confidence indicators, and leading post-incident analysis that informs architectural and process improvements
• Produce exemplary technical artifacts — quality architecture documents, automation frameworks, test platforms — that set the bar for the rest of the team, while staying hands-on in critical quality systems and automation code paths
• Serve as the accountable technical leader for strategic initiatives, proactively managing reliability, scalability, and technical debt across teams
• Mentor senior SDETs, quality engineers, and other senior technical leaders — especially on building AI fluency into their practice
• Establish hiring standards, coaching, and talent development
• Champion customer-centric quality decisions, ensuring technical trade-offs reflect real user needs and long-term product value
• Partner with Engineering and Product leadership to embed scalability and resilience into roadmap planning, not just technical design

Benefits

• Generous PTO: Take the time you need, when you need it - including generous parental leave
• Full healthcare: High-coverage medical, dental & vision coverage for individuals and families
• Retirement planning: Take advantage of our 401(k) plan including contribution matching
• Work from anywhere: We are a remote-first company, so you can work from anywhere you like in the uS
• Robust compensation: We offer competitive salary bands and stock options
• Employee discount: Employees can take advantage of product discounts
• Utility stipend: A extra $75 each month to cover extra cell phone, internet, or data usage
• Spending accounts: Options for additional HSA and FSA plans to help toward healthcare costs

• 10+ years of hands-on experience in quality engineering or SDET roles, including experience architecting quality strategy and automation platforms across multiple teams
• Excellent judgment on trade-offs between short-term delivery and long-term system resilience and maintainability
• Hands-on experience applying AI to testing — LLM-assisted test generation, agent-based workflows, intelligent test selection, or self-healing automation — with informed opinions about where it delivers and where it disappoints
• Experience mentoring and developing senior quality engineers and senior technical leaders, with a track record of raising the technical bar across a group or organization
• Experience with performance and load testing at scale
• Strong grasp of modern development and delivery practices (agile/lean, DevOps, shift-left testing, TDD) and experience embedding quality gates into CI/CD systems (e.g., GitHub Actions, CircleCI, Jenkins)
• Deep proficiency in one or more programming languages (e.g., JavaScript, TypeScript, Kotlin) used to build and maintain shared automation frameworks and tooling. You write production-quality code, not just test scripts
• Proven track record designing and scaling test automation frameworks across the full stack — frontend web, mobile, and backend/API (e.g., Playwright, Cypress, Selenium, Appium, Postman, or similar)
• Demonstrated ability to define quality architecture and standards that scale across many teams, including shared quality platforms and test infrastructure
• History of leading post-incident and root-cause analysis that drives architectural and process change
• Strong executive communication skills, with the ability to influence engineering and product leadership on quality strategy, risk, and investment
• We are committed to building a workforce that reflects diverse perspectives and prioritizes ethics, wellness, and a strong sense of belonging. If you’re excited about this role, we encourage you to apply—even if you’re not sure if your background or experience is a perfect match
• Published writing, talks, or open-source work on modern testing practice or AI in quality engineering
• Familiarity with LLM observability and evaluation tooling (e.g., Braintrust, Arize, MLflow, LangSmith, or similar)
• A track record of building quality engineering communities of practice — tech talks, katas, lunch-and-learns
• Experience with cloud-based testing platforms and tools (e.g., AWS Device Farm, Sauce Labs, BrowserStack)
• Familiarity with e-commerce or healthcare platforms and quality-at-scale practices in regulated environments
• Experience building evaluation or testing infrastructure for LLM-based or ML-driven product features (e.g., eval harnesses, LLM-as-judge scoring, regression testing for non-deterministic systems)
• Experience with internationalization and localization testing