As Senior Risk Manager within the Azurion Eye program, you own and continuously evolve the product risk management strategy across the complete product lifecycle. You ensure that AI-enabled, cloud-based, and connected medical solutions are developed and maintained in line with applicable safety, quality, and regulatory requirements.
Your role
- Lead product risk management activities from early concept and architecture through development, regulatory submission, post-market surveillance, and continuous software releases.
- Develop and maintain the Product Risk Management File in accordance with ISO 14971 and Philips QMS requirements.
- Lead hazard analyses, benefit-risk assessments, software risk analyses, and AI risk assessments.
- Define safety strategies for AI-enabled SaMD, SaNMD, cloud-native software, connected medical devices, and distributed services.
- Facilitate cross-functional risk workshops with Engineering, Clinical, Quality, Regulatory Affairs, and Product Management.
- Integrate risk management into Agile, DevSecOps, CI/CD, and software lifecycle practices.
- Use complaint data, software telemetry, clinical feedback, and AI performance monitoring to support product safety decisions.
- Support regulatory submissions, audits, CAPA investigations, field actions, and post-market surveillance.
- Coach development teams and promote a strong product safety culture.
You're the right fit if:
- A Master's or PhD in Biomedical Engineering, Systems Engineering, Software Engineering, Computer Science, or a related field.
- At least 8 years of experience in regulated medical device development.
- Extensive experience leading risk management for software-intensive medical devices.
- Experience with AI-enabled SaMD, connected healthcare systems, cloud-native software, and distributed architectures.
- Strong knowledge of ISO 14971, IEC 62304, IEC 82304-1, ISO 13485, IEC 81001-5-1, FDA QMSR, and EU MDR.
- Experience with cybersecurity risk management, regulatory submissions, audits, and post-market surveillance.
- Strong stakeholder management skills and the ability to influence cross-functional engineering teams.
- Excellent written and verbal communication skills in English.
Nice to have
- Experience with MLOps, computer vision, foundation models, or large language models.
- Knowledge of AI performance, bias, explainability, model drift, human oversight, and AI governance.
- Experience with Azure or AWS, Kubernetes, containerized application