Product Manager – AI Efficiency

bol

Utrecht

1 week ago

Utrecht

1 week ago

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Product Manager – AI Efficiency

Product Manager needed for the newly formed AI Efficiency team at bol, responsible for introducing AI agents to automate operational workflows. Requires 5+ years of product management experience with platform, automation, or AI-enabled products, and practical understanding of AI and LLMs. Role involves defining product strategy, redesigning processes, and collaborating with cross-functional teams.

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Hybrid

Full-time

Senior

LLMs

Salary

Not specified

Work Location

Utrecht, Utrecht, Netherlands, NL

Work Model

Hybrid: 50% at the office and 50% at home

Experience Required

5 years

Employment Type

Full-time

Experience Level

Senior: 5+ years of product management experience

Core Qualifications

Technical (Must-have)

AILLMsautomation

Soft Skills

product thinkingoutcome focuscollaborationpragmatismstakeholder management

Key Responsibilities

•Define and evolve the product vision for AI-driven operational efficiency, translating it into a roadmap with measurable outcomes
•Partner with operational teams to deeply understand existing workflows, then redesign them to streamline automation and grow impact
•Drive standardization and modularity so that agentic capabilities are reusable across categories and domains
•Work with engineers and data scientists to ship secure, traceable AI agents with humans in the loop, clear evaluation criteria, and appropriate guardrails
•Define success metrics and build feedback loops that focus on real impact
•Conduct experiments, scale what works, kill what doesn't, and make trade-offs transparent to stakeholders
•Help shape the team: contribute to hiring decisions, define ways of working, and build a culture of product thinking and measurable outcomes

Product ManagerAIEfficiencyHybridUtrechtFull-timebolAutomationLLMsPlatform

Key Responsibilities

•Define and evolve the product vision for AI-driven operational efficiency, translating it into a roadmap with measurable outcomes

•Partner with operational teams to deeply understand existing workflows, then redesign them to streamline automation and grow impact

•Drive standardization and modularity so that agentic capabilities are reusable across categories and domains

•Work with engineers and data scientists to ship secure, traceable AI agents with humans in the loop, clear evaluation criteria, and appropriate guardrails

•Define success metrics and build feedback loops that focus on real impact

•Conduct experiments, scale what works, kill what doesn't, and make trade-offs transparent to stakeholders

•Help shape the team: contribute to hiring decisions, define ways of working, and build a culture of product thinking and measurable outcomes