Head of Quality Engineering

Rad AI is on a mission to transform healthcare with AI-driven solutions for radiology. This role leads Rad AI's Quality organization to ensure radiologists can trust AI in their daily work. The role will be based in the San Francisco office, with employees expected to work onsite four days per week; the remaining time may be remote or onsite, depending on team and business needs.

Responsibilities

Lead Rad AI's Quality organization, reporting to the CPO; Lead one Quality team while keeping quality engineers embedded in product teams, running a shared operating cadence, priorities, standards, and roadmap; Own the quality system (strategy, risk assessment, tooling, environments, coaching, visibility) so developers own the quality of what they build; Bring quality into planning with Product, Engineering, Design, and Clinical; Make release readiness risk-based, including a pre-release risk assessment, radiologist persona test cases, a common smoke-test baseline, and an org-wide definition of "ready to ship"; Close the gap between green tests and the customer experience using radiologist personas, shadowing, customer recordings, product telemetry, and customer-matched environments; Keep the test signal trustworthy by owning failure triage, flaky-test quarantine policy, and stable test environments; Make quality visible through metrics (customer-found vs. internally found defects, escaped defects, change failure rate, test stability, time to detect), quality OKRs, a company-level quality dashboard, and quarterly quality reviews; Turn incidents and escaped defects into prevention with incident review owners, Support, and Customer Success; Define how to evaluate non-deterministic AI outputs such as speech recognition and generated impressions; Embed clinical risk and compliance into quality with Clinical, Security, and Compliance (HIPAA, auditability, regulatory expectations for clinical AI); Codify and share quality standards through a Quality community of practice, Quality Week, office hours, and demos; Hire, coach, and grow quality engineers, own the Test Automation Engineer career framework, and manage quality tooling, vendors, and test infrastructure cost-effectively

Requirements

10+ years in software quality and test engineering, including 5+ years leading quality teams; 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 by spreading what works; Strong hands-on foundation in test automation (end-to-end, API, and desktop or Electron UI automation in CI/CD pipelines, plus test environments); Able to go deep on test architecture and flaky-test root causes; Experience shifting quality left, where engineers own quality and quality never becomes the gate; Data-driven approach with experience defining quality metrics (escaped defects, change failure rate, test stability), setting OKRs, and moving them; Experience with risk-based testing for integration-heavy products running across many customer configurations and environments; Ability to build a long-term quality roadmap and broker decisions with engineering leaders on architecture and testability; Excellent communication across technical and non-technical audiences, with a track record of influencing Engineering, Product, Support, and executives without formal authority; Expert hiring and people management for distributed teams across time zones; Experience managing quality tooling and vendor relationships (test management platforms, outsourced QA, test environment providers); Asks great questions, starts with the smallest change that adds value, and uses AI tools to make quality work faster and broader

Nice to have

Experience in healthtech or a regulated environment (HIPAA, PHI, SOC 2), ideally with medical device software practices (SaMD, IEC 62304, ISO 14971 risk management); Familiarity with radiology workflows and systems (PACS, RIS, EHR, dictation platforms such as PowerScribe or Fluency, HL7/FHIR, FHIRcast, DICOM); Evaluated ML or AI systems in production, such as speech recognition accuracy or generated-text quality; Owned performance, load, or reliability testing and partnered closely with incident management; Led a multi-team quality organization, including managers or Staff-level engineers; Built or scaled a quality function at a high-growth startup

Benefits

Comprehensive Medical, Dental, Vision & Life insurance; HSA (with employer match), FSA, & DCFSA; 401(k); 11 Paid Company Holidays; Flexible PTO policy; Annual company-wide offsite; Periodic team offsites; Annual equipment stipend