Senior Software Design Quality Engineer - AI
In this role, you have the opportunity to
As a highly experienced Senior Design Quality AI Engineer, you will lead design assurance activities for complex software-driven and AI-enabled products, ensuring the highest standards of safety, performance, compliance, and reliability. You will act as a strategic technical SME within the organization, partnering cross-functionally with Engineering, Product Management, Data Science, Cybersecurity, Clinical/Regulatory, and Manufacturing teams to embed quality and compliance throughout the product lifecycle.
You are responsible for
Design Quality Engineering Expertise
- Lead Design Quality Engineering activities for assigned projects across the full software product lifecycle—from concept to commercialization.
- Drive compliance with design control processes (e.g., ISO 13485, IEC 62304, ISO 14971, IEEE 1633, and AI regulation frameworks such as EU AI Act-ready practices).
- Act as key partner for defining and maintaining quality strategies and KPIs for complex, multi-component systems integrating software, cloud, data, and AI/ML in compliance with applicable regulations and standards.
Software & AI Quality Assurance
- Oversee quality planning, documentation, and reviews for software and AI-enabled solutions (including foundation models and prompt engineering).
- Design quality assurance for deep neural networks and governance of training pipelines (for reproducibility).
- Ensure robust validation strategies for artificial intelligence models, including dataset quality, model performance, bias detection, and continuous learning.
- Partner with R&D teams to ensure transparency, explainability, and traceability in AI model development.
Risk Management & Compliance
- Oversee risk management activities per ISO 14971, including hazard analyses, FMEAs, fault tree analyses, cybersecurity risk assessments, and AI-specific risks.
- Evaluate design robustness and reliability using data-driven methods and statistical techniques.
Technical Reviews & Design Assurance
- Collaborate with R&D and conduct expert-level design reviews on architecture, algorithms, code, test strategy, and verification/validation evidence.
- Identify gaps early in the design and drive cross-functional remediation.
- Serve as a quality SME during regulatory submissions and audits.
Process Excellence & Continuous Improvement
- Mentor teams in quality engineering best practices.
- Support development of advanced processes for AI product lifecycle, dataset governance, software traceability, DevOps, and continuous quality monitoring.
- Champion a culture of “Quality by Design” across R&D.
You are a part of
You will be part of the global Philips Q&R organization and will be reporting within the Design Quality team for IGT-Systems. As a member of this team, you contribute to our constant strive for a shift-left approach and further product quality improvements, so we continuously exceed both internal and external stakeholder expectations.
To succeed in this role, you should have the following skills and experience
We are looking for a self-motivated and skilled individual who continuously strives for excellence as a way of life, not just as a job, and who can inspire others to prioritize quality above all else in a relentless pursuit to improve quality of life.
Specific skill requirements for this role include:
- Bachelor's (Master’s preferred) degree in Software Engineering, Computer Science, or related field with 15+ years of experience.
- Experience in new product development and LCM projects as a Design Quality Engineer.
- Technical skills in C++, C#, Python, or other programming languages (a plus).
- Sound understanding of the regulatory landscape including ISO 13485, ISO 14971, IEEE 1633, FDA Drugs and Cosmetic Act (CFRs), IEC 62304, and AI-related requirements.
- Sound understanding of AI foundation models, prompt engineering, and data processing techniques.
- Experience with automated testing tools and frameworks (e.g., Selenium, JUnit, PHPUnit).
- Excellent analytical and problem-solving abilities.
- Proven ability to lead and mentor teams in a collaborative environment.
- Strong communication skills (written and verbal), with the ability to convey complex technical concepts to non-technical stakeholders.
- Experience with Agile methodologies and tools.
- Knowledge of regulatory standards and compliance related to software quality assurance and AI.