Internship: AI Agents for Systems Quality Engineering

This internship opportunity is within the Systems Quality Engineering (SysQE) team at Philips Innovation Engineering, focused on applying quality engineering methods in a regulated medical technology environment.

The team supports engineering teams and works on topics such as requirements quality, design quality, risk management, design reviews, DFMEA/PFMEA support, design verification, process validation, and quality decision-making across the product development lifecycle.

Within this engineering quality environment, AI agents can increasingly support productivity, consistency, and technical decision-making. Many opportunities exist to help engineers find, interpret, and apply quality knowledge more effectively. However, turning these ideas into robust, maintainable, scalable, and trusted AI-agent solutions remains a challenge.

This internship focuses on understanding and improving the full lifecycle of AI agents in Systems Quality Engineering — from idea and use-case definition to prototype, evaluation, documentation, and potential reuse. To enable fast experimentation and learning, the internship can initially focus on agent concepts that do not require deep domain expertise, before extending to more SysQE-specific use cases.

Job Description

• Understand SysQE workflows and identify where AI agents can support or assist engineers and quality specialists.
• Analyze existing or conceptual AI-agent ideas and their underlying assumptions.
• Select one or more practical use cases with clear value for Systems Quality Engineering.
• Design and implement simple agent prototypes or agent-supported workflows to test different approaches.
• Evaluate agent behavior, usability, maintainability, reliability, source traceability, and integration aspects.
• Experiment with interaction, reuse, or orchestration between multiple agents, prompts, knowledge sources, or workflows.
• Involve SysQE engineers and relevant stakeholders to check practical usefulness and learn from real engineering needs.
• Document findings, design choices, patterns, limitations, and lessons learned.

Based on the insights gained, the student will propose and prototype new or improved agents, demonstrating how Systems Quality Engineering knowledge can be transformed into practical, usable, and sustainable digital support.

You're the right fit if:

• You are currently pursuing a Master degree in Computer Science, Software Engineering, AI, Data Science, Systems Engineering, Industrial Engineering, Biomedical Engineering, or a related field.
• You have interest in AI agents, automation, applied software engineering, knowledge management, and engineering quality.
• You have knowledge of statistics.
• You are comfortable with experimenting, learning by doing, and working in an exploratory setting.
• You have the ability to translate complex information into practical solutions.
• You have good communication skills and willingness to interact with engineers, quality specialists, and stakeholders.
• You are a self-starter, clearly state your opinion, act sharply, and like redesigning processes.
• Experience with Python, Microsoft 365 Copilot, Copilot Studio, Power Platform, prompt engineering, or AI-agent frameworks is a plus.
• Experience or interest in medical technology, quality engineering, systems engineering, risk management, or regulated product development is a plus.

Philips is a health technology company focused on expanding access to quality healthcare and helping improve access to quality healthcare.