AI Product Manager

About this role

At Workwize, we’re helping IT teams to easily equip their remote and global teams with all necessary IT equipment. Our automated SaaS platform simplifies hardware deployment, management, and retrieval with fast, reliable deliveries in 100+ countries. With 50.000 users and 120.000 devices under management, we’re solving hybrid work challenges like laptop deliveries, returns and equipment tracking, allowing IT teams to focus less on manual hassles and more on strategic initiatives.

Join our team to help shape the future of global collaboration. At Workwize, your work will make a real impact in building smarter, more connected workplaces worldwide. LinkedIn has also recognized Workwize as one of the Top 10 Startups for 2025 in the Netherlands! About the Role We are looking for an AI Product Manager who wants to build intelligent automation into a real, complex operational product. At Workwize, we help companies set up, manage, repair, retrieve, and store IT equipment for distributed teams across 100+ countries.

That means lots of workflows, lots of edge cases, and a massive opportunity to use AI to eliminate manual work for IT managers. In this role, you will own the product vision for how AI agents and automation transform our platform. You will work hands-on with AI tooling to design, build, and continuously improve agents that handle complex operational workflows. This is not a strategy-only role. You will be in the details, working with tools like LangSmith to trace agent behavior, evaluate outputs, and systematically make our AI features more reliable and effective.

If you get excited about building AI agents that actually work in production, and you care about making them better every week, we want to talk to you. Responsibilities Strategy & Product Vision • Own the AI roadmap and identify where AI can automate and improve operational workflows across the Workwize platform. • Track relevant advances in AI agents and automation, and turn them into clear product bets. Build, Ship, Improve • Partner with Engineering to design and ship AI-powered features into production.

• Define agent behavior (workflows, prompts, guardrails) and handle real-world edge cases across customers and regions. • Own production quality: monitor performance, investigate failures, and improve reliability over time. • Set up evaluation and feedback loops, and track KPIs such as time saved, accuracy, adoption, and customer satisfaction. Collaboration • Partner with Engineering, Operations, and Customer Success to understand workflows, align priorities, and deliver outcomes.