AI-First Senior QA Engineer

Everlywell is a digital health company pioneering the next generation of biomarker intelligence-combining AI-powered technology with human insight to deliver personalized, actionable health answers. We transform complex biomarker data into life-changing insights-seamlessly integrating advanced diagnostics, virtual care, and patient engagement to reshape how and where health happens.

Over the past decade, Everlywell has delivered close to 1 billion personalized health insights, transforming care for 60 million people and powering hundreds of enterprise partners. In 2024 alone, an estimated 1 in 86 U.S. households received an Everlywell test, solidifying our spot as the #1 at-home testing brand in the country. And we're just getting started. Fueled by AI and built for scale, we're breaking down barriers, closing care gaps, and unlocking a more connected healthcare experience that is smarter, faster, and more personalized.

We're looking for a Senior QA Engineer who thrives in an AI-first engineering culture - one where artificial intelligence is not just a tool, but a force multiplier that enhances speed, creativity, and coverage in quality assurance. In this role, you'll own the development and automation of test cases and test infrastructure, and you'll leverage AI to accelerate and augment every aspect of QA : from generating tests based on product specs to writing and maintaining automated test suites, and surfacing insights from bugs and data anomalies.

You'll collaborate closely with engineering, product, and design to ensure a culture of quality is embedded from day one, and your AI-enhanced workflows will set the bar for what a modern QA practice can achieve.

What You'll Do :

• Use AI tools like Cursor to rapidly generate test cases from requirements, user stories, and code diffs.
• Build and maintain automated end-to-end test suites using frameworks like Cypress, Playwright, or Selenium, with AI assistance to speed up development and catch edge cases.
• Integrate AI-driven static analysis, code coverage tools, and anomaly detection into CI / CD pipelines.
• Define and manage test strategies for new product features with a focus on AI-augmented speed and accuracy.
• Use LLMs and agents to simulate user behavior for broader scenario coverage.
• Continuously evaluate and implement AI-powered QA platforms to improve regression, smoke, and exploratory testing.
• Collaborate with engineers on shift-left testing practices, pairing during development to catch issues early.
• Monitor application performance, errors, and logs using tools like Sentry, DataDog, or equivalent - augmented by AI-powered alerting and triage.
• Contribute to defining AI-first QA best practices, playbooks, and tooling standards across the team.

Who You Are :

Nice to Have :