Modern radiology AI for reporting, impressions and follow-up. Reduce cognitive burden, improve report quality and help radiologists work faster. Backed by Khosla.
About the role
Our principle is simple: Engineering owns quality; Quality owns the quality system. You'll lead that system, spreading what already works rather than rebuilding it. You'll make release risk explicit, bring real radiologist workflows and customer environments into how we test, and make quality visible from the team level up to the executive team. The team you build will define how clinicians trust AI in their daily work. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- 10+ years in software quality and test engineering, including 5+ years leading quality teams, with a track record of building a quality function and staffing it cost-effectively as the company grows
- Experience taking over a capable but inconsistent quality organization and raising the bar across teams by spreading what works, not rebuilding it
- A strong hands-on foundation in test automation (end-to-end, API, and desktop or Electron UI automation in CI/CD pipelines, plus test environments), and you can still go deep on test architecture and flaky-test root causes
- Experience shifting quality left: engineers own quality, the quality team builds the system, and quality never becomes the gate everyone waits on
- A data-driven approach: you've defined quality metrics such as escaped defects, change failure rate, and test stability, set OKRs against them, and moved them
- Experience with risk-based testing for integration-heavy products that run across many customer configurations and environments
More about this role
At Rad AI, we’re on a mission to transform healthcare with artificial intelligence. Founded by a radiologist, our AI-driven solutions are revolutionizing radiology—saving time, reducing burnout, and improving patient care. With one of the largest proprietary radiology report datasets in the world, our AI has helped uncover hundreds of new cancer diagnoses and reduced error rates in tens of millions of radiology reports by nearly 50%.
Rad AI has secured over $140M in funding, including a recently oversubscribed Series C ($68M round) led by Transformation Capital, bringing our valuation to $528M. Our investors include Khosla Ventures, World Innovation Lab, Gradient Ventures, Cone Health Ventures, and others—all backing our mission to empower physicians with cutting-edge AI.
Our latest advancements in generative AI are used by thousands of radiologists daily, supporting more than one-third of radiology groups and healthcare systems and nearly 50% of all medical imaging in the U.S. at partners including Cone Health, Jefferson Einstein Health, Geisinger, Guthrie Healthcare System, and Henry Ford Health.
Recognized as one of the most promising healthcare AI companies by CB Insights and...
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