64K–101K EUR / year
Director of Quality Engineering
QAWorkplace — unknown
Published on 2026-11-02
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About this role
Lead end-to-end quality strategy for Sword’s medical-device software, AI/ML, and connected-device products. Shape verification and validation, test automation, and release practices so teams can deliver quickly while meeting regulatory requirements.
About the company
Sword Health is a digital musculoskeletal care company that helps employers and health plans deliver AI-powered physical therapy and related care programs.
What you'll do
- Define quality strategy across web, mobile, backend, firmware/hardware integration, and AI products
- Own SaMD verification and validation strategy, including traceability from requirements and risk controls to test evidence
- Define AI/ML testing and monitoring for model performance, datasets, bias, robustness, regressions, and post-deployment drift
- Embed shift-left practices, CI/CD quality gates, and automated regression, performance, security, and accessibility testing
- Align engineering processes with the Quality Management System and support regulatory audits
- Drive risk analysis and verification of risk controls with product and clinical teams
- Evaluate test management, automation, and traceability tools
What we're looking for
- 7+ years in software quality engineering, including 5+ years leading quality organizations in regulated environments
- Experience with medical-device software or comparable regulated domains
- Working knowledge of IEC 62304, ISO 13485, ISO 14971, ISO/IEC 42001, IEC 81001-5-1, and FDA 21 CFR Part 820/QMSR and/or EU MDR
- Track record scaling test automation and CI/CD quality practices across product teams
- Experience defining V&V strategies and producing evidence for audits or regulatory submissions
- Technical credibility to review architectures, test frameworks, and code, and coach engineers
- Experience hiring, mentoring, and leading technical quality teams
- Strong communication and influence skills across executive, engineering, clinical, and regulatory stakeholders
Nice to have
- AI fluency, with examples of using AI in work; expected proficiency depends on role seniority