AI Product Manager — Computer Vision & Data Platform

ACV Auctions; Paris; Hybrid; EUR 70,000 - 110,000; Full time

Job summary

Monk AI is seeking a Product Manager to lead a key product team within its vehicle damage detection platform in Paris. You will shape the product strategy, own the roadmap, and work cross-functionally with developers, data scientists and other partners to deliver value.

Responsibilities include planning with the tech lead, translating needs into clear specs, prioritising features, owning QA, and running ceremonies like backlog grooming and sprints.

Qualifications

• 3+ years of product management experience leading technical teams (data science/engineering).
• Proven ability to lead a technical team and make calls without being the domain expert on every topic.
• Experience with B2B / enterprise client relationships.
• Solid understanding of data/AI topics; computer vision is a plus.
• Hands-on experience with Python, SQL, and big data queries.
• Comfortable with vibe coding and working with LLMs.

Responsibilities

• Drive product strategy and the roadmap for their area of ownership.
• Take full ownership of a technical team product scope (developers, data scientists).
• Work with the tech lead on planning and delivery management.
• Scope product evolutions with technical teams and translate needs into clear specifications.
• Prioritize features based on value and constraints.
• Own quality assurance and facilitate key product ceremonies (backlog grooming, sprint planning, reviews).
• Test new ideas by implementing quick POCs.

Skills

Product management

Technical leadership

B2B relationships

Data/AI knowledge

Python

SQL

LLMs

Job description

Monk AI is seeking a Product Manager to lead a key product team within its vehicle damage detection platform in Paris. You will shape the product strategy, own the roadmap, and work cross-functionally with developers, data scientists and other partners to deliver value.

Responsibilities include planning with the tech lead, translating needs into clear specs, prioritising features, owning QA, and running ceremonies like backlog grooming and sprints.