Qonto - Senior Product Manager for our AI Lab
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Requirements
• 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. • ➡️ 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. • At Qonto, we understand that true diversity isn’t just about ticking boxes on a hiring checklist. Apply regardless of the boxes you tick — who knows? You may have the missing piece of the puzzle we’ve been searching for all along. • By applying, you agree that Qonto processes your personal data to assess your application. Your data is kept for up to 2 years in our candidate pool. Read our Privacy Notice for full details. • ----------------------------------------------------------------------------------------------------- • On average, our hiring process lasts 20 working days. More information on our candidate journey here • 🔒 Your security matters to us • Recruitment scams are on the rise. Keep in mind, we will never work with third-party platforms or agencies that request payment from candidates. • If you receive a suspicious message claiming to be from Qonto, please report it right away ([email protected]) • We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Responsibilities
• 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.
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