Senior Backend Product Engineer - Python/Go [AI LAB]

Our mission and customers: We are creating the freedom for SMEs to succeed by delivering Europe's leading finance workspace with banking at its core, augmented by financial tools. We are proud to be rated 4.8 on Trustpilot, based on 55,000+ reviews. Our culture puts customer satisfaction at the core of what we do, as proven by our Net Promoter Score of 75. Our journey: Founded in 2017 by Alexandre and Steve, Qonto has grown to 1,600+ Qontoers serving over 600,000+ customers across 8 European countries. We have been profitable since 2023, and we are just getting started. Our beliefs: We hire for skills and potential. With 80+ nationalities, 45% women, of which 56% of women in our leadership team, diversity isn't a program; It's who we are. We've built a discrimination-free hiring process because the best teams are built on merit. AI at Qonto: AI is deeply embedded in how we work (here) - Every Qontoer gets unlimited access to the best AI tools. We want people who experiment without waiting for permission, push AI beyond the obvious, know when to trust it, and when to question it. ------------------------------------------------------------------------------------------------------ 🌍 This job is open to full remote if you are based in France, Germany, Italy, or Spain.  ⭐ Mission Join our AI Lab as a SeniorBackend Product Engineer and help accelerate Qonto's transition to an AI-first product. You'll ship user-facing AI agents that transform how 600,000+ businesses manage their finances, working in small, autonomous squads under the guidance of Sophie, our Manager for the AI Lab. With an ambitious goal to launch one AI agent every 6 weeks, you'll own the backend and AI logic end-to-end — building reliable, maintainable systems that scale as the Lab grows.  👩‍💻 As a Senior Backend Engineer for the AI Lab, you will Ship fast and well: Build & deliver a new AI agent every 6 weeks, owning the full backend and AI logic from scoping to deployment — balancing speed with reliability and minimal technical debt. Build for the long term: Architect pragmatic LLM guardrails and future-proof components that hold up in a regulated banking environment and don't need rewriting three months later. Leverage AI daily: Use AI coding tools (Cursor, Claude Code, Copilot…) for ~70% of your coding to review, refine, and ship features faster. Go full-stack when it counts: Contribute to frontend (React/JS) when needed, with the FE engineer reviewing your PRs — so the squad stays unblocked. 🏅 What we're looking for Python expertise: You have strong production experience in Python and know how to ship at pace — Go/RoR knowledge is a plus for integrating with Qonto's core services. Go or Ruby on Rails knowledge: Qonto's core services are built on Go and Ruby — working knowledge of either will make you significantly more effective integrating with the broader platform. Startup mindset: You're a fast learner and confident shipper who comes from a product-driven, user-centric environment and thrives without a tech lead to lean on — fintech or regulated industry experience is a plus. AI-native workflow: You use AI coding tools daily to amplify your output. Cursor or Claude Code isn't something you're trying — it's how you work. AI curiosity over AI expertise: Production AI experience isn't required. What matters is genuine curiosity: you follow the space, experiment on the side, and have tried building something, even just for yourself. Strong communication: You articulate technical decisions clearly to non-technical stakeholders and navigate cross-functional squads with ease. 🔧 What you'll get Unlimited access to the best AI toolson the market: Claude Code (with the Superpowers plugin), Cursor, Copilot, Notion AI. A Python-first stack with hands-on AI agent work from day one — PydanticAI, LangGraph, LangChain in the mix (framework awareness appreciated; production expertise not required). A lean culturewhere autonomy is the default — you're building the agents, not just using them, owning the outcome end to end in a squad with minimal process and every hour counting. A clear growth path: this role is designed to evolve toward an AI Software Engineer role. If becoming an AI-native engineer is your ambition, this is where it happens. 🤝 About 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. Steve, one of our founders, attends Friday demos regularly. 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. 💬 Hiring Process 2 Interviews (1 hour each): first with your Talent Acquisition Manager, and then with one of our Backend Leads Technical case + debrief with two Backend engineers (1 hour) Final interview and meeting with Sophie (1 hour) We aim to wrap the process in 10 days max, from first interview to potential offer 🤞 If you've read this far and thought "that sounds like me but I don't check every box" — apply anyway. We hire on potential and mindset, not checklists. 🔒 Your security matters to us Recruitment scams are on the rise. 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 at support@qonto.com.