Original listing text, shown exactly as published by the company.
➡️ What you'll do
- Own an AI agent end-to-end: Drive the full lifecycle — discovery, prioritization, spec, delivery, iteration — for 1–2 agents at a time, from first hypothesis to live product.
- Set and hold the delivery cadence: Define what "done" looks like, track progress, and unblock the team — without waiting for someone else to push.
- Talk to users, constantly: Regular user calls are non-negotiable. They're how you validate problems, catch signal early, and build agents people actually use.
- Partner with domain experts: Work with cross-functional teams (e.g., Financing for banking agents) to acquire the context you need and co-define features with the people closest to the problem.
- Help scale agent practices: Contribute to the patterns, handover models, and playbooks that will eventually let AI agents live across Qonto's product organization.
➡️ What we're looking for
- End-to-end ownership (L3+): You've shipped products from problem to production, and you own the outcome — not just the coordination. Blockers don't wait for others; you solve them.
- Strong user-driven mindset: You talk to users regularly, not occasionally. You turn qualitative signals into sharp problem statements and concrete decisions.
- PM fundamentals: Product sense, prioritization, structured thinking, and the ability to manage stakeholders across a cross-functional environment.
- Positive influence on engineering teams: You set a high bar and keep pressure healthy — energizing, not draining. Engineers want to work with you.
- AI curiosity and fluency: You use AI tools daily (Claude, Dust, or similar), follow the space, and have ideally built a small agent or automation of your own.
French speaker
➡️ What you can expect
- An "agent highway" already built: The AI Lab has existing infrastructure, UI patterns, and agent frameworks. You're building on a real foundation — at speed, not from scratch.
- A technically dense team: ~10 engineers, a designer, and a PMM, all focused on AI agents. Steep learning curve, high signal density, fast feedback loops.
- Broad, meaningful scope: The agents you'll own can span large domains (e.g., a banking advisor with multiple capabilities). The impact is company-wide, not siloed.
- Room to shape how AI scales at Qonto: As the Lab matures, PMs here will influence how agent ownership transitions across teams. You'll help define what that model looks like.
- Ship fast, ship well: The AI Lab runs at a cadence you'll rarely find elsewhere — without trading quality for speed. Here’s how we build.
➡️ Your future manager
You'll work closely with Sophie, Manager of the AI Lab — but don't expect hand-holding.
Sophie has led cross-functional teams through the full product lifecycle at both fast-growing startups and established tech companies. She partners directly with Product and Tech leadership to align the AI roadmap with Qonto's strategic goals.
Her approach: give engineers real ownership, create space for experimentation, and empower the squad to adapt their ways of working in pursuit of real impact.
