AI Product Manager – Enterprise Informatics at Philips
Amsterdam, , Netherlands -
Full Time


Start Date

Immediate

Expiry Date

04 Oct, 25

Salary

0.0

Posted On

05 Jul, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Good communication skills

Industry

Information Technology/IT

Description

ABOUT US – ENTERPRISE INFORMATICS AT PHILIPS

At Philips, our Enterprise Informatics (EI) business powers smarter healthcare through intelligent, secure, and connected software solutions. From diagnostic imaging to EMR integration and real-time clinical decision support, we help hospitals and health systems unlock the power of data to improve care.

WHAT TO EXPECT IN THE INTERVIEW PROCESS:

Candidates may complete a case interview to showcase how they would approach a real-world AI use case – defining value, prioritizing scope, and framing the solution. We’re looking for structured thinking, product intuition, and a bias for clarity and action.

Responsibilities

YOUR ROLE

We’re not building more apps – we’re transforming how we work. As AI Product Manager, your mission is to embed AI across internal tools and processes to make work radically simpler and faster. From automation to augmentation, your job is to give the repetitive tasks to machines and free people up to do more meaningful work. Your impact will span teams and domains, helping EI become a best-in-class, AI-first organization from the inside out.

WHAT YOU’LL DO:

  • Identify high-impact AI use cases across internal domains – from R&D and product to sales, marketing, service, and delivery
  • Define the AI-first north star for each domain, set measurable success criteria, and identify/prioritize AI use cases to help us get there
  • Translate problems into clear product requirements – owning epics, features, and user stories to guide development
  • Partner with external organizations to benchmark, co-develop solutions, and understand what “great” looks like
  • Drive make-vs-buy decisions based on strategic fit, speed, and scalability
  • Lead end-to-end development of AI use cases – working closely with AI squads/DevOps and external partners to deliver scalable, usable, and lovable solutions
  • Define success metrics, measure impact, and continuously iterate to improve
  • Champion an AI-first culture – Lead the AI-in-EI Center of Excellence and embed AI thinking into how we work across the business
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