Hims and Hers Senior Staff SDET responsible for owning quality architecture and engineering strategy for critical systems at Hims & Hers. Lead AI application across testing and release pipelines to build AI-native quality systems.
Responsibilities
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.
Why This Role Is Different
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 and 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.
Qualification
Strong executive communication skillsPublished writing
Required
10+ years of hands-on experience in quality engineering or SDET roles, including experience architecting quality strategy and automation platforms across multiple teams.
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).
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.
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.
Demonstrated ability to define quality architecture and standards that scale across many teams, including shared quality platforms and test infrastructure.
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).
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.
History of leading post-incident and root-cause analysis that drives architectural and process change.
Excellent judgment on trade-offs between short-term delivery and long-term system resilience and maintainability.
Strong executive communication skills, with the ability to influence engineering and product leadership on quality strategy, risk, and investment.
Experience with performance and load testing at scale.
Preferred
Familiarity with LLM observability and evaluation tooling (e.g., Braintrust, Arize, MLflow, LangSmith, or similar).
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 with internationalization and localization testing.
A track record of building quality engineering communities of practice — tech talks, katas, lunch-and-learns.
Published writing, talks, or open-source work on modern testing practice or AI in quality engineering.
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).