Senior/Staff Backend Engineer - AI Compliance Tooling

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 (more about our culture here). 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. ------------------------------------------------------------------------------------------------------ 🌏 Location: France, Germany, Spain, or Italy — full remote-friendly. Join us as a Senior Backend Engineer to build the AI-powered tooling that enables Qonto's financial crime compliance teams to make decisions faster and with greater confidence, directly supporting our path to a full banking licence. ➡️ As a Backend Engineer at Qonto, you will Build AI-integrated backend systems: Design and ship production-grade services that connect AI models (Claude, OpenAI, or open-source equivalents) to our compliance workflows, handling prompting, output parsing, and model behaviour in a real regulated-industry context Own service architecture end-to-end: Co-own design, reliability, and scalability from day one, no PM layer between you and the technical decisions that shape the product Automate AML/AFC compliance operations: Translate compliance agent workflows into software, from EDD automation to customer onboarding acceleration, with direct feedback from the ops teams you're helping Drive continuous improvement: From production monitoring to post-mortems, you track impact, flag regressions, and improve what's in your scope with your peers and manager Shape the technical direction: In a team of 5, every engineer carries architectural weight. You'll lead design discussions, anticipate risks, and contribute to how the platform evolves ➡️ What you can expect Short time-boxes and lean process: daily goals, light Kanban, ceremonies, you spend most of your time building, not in planning meetings AI is the product, not a side tool: this team's output is AI-powered compliance tooling. You'll use Claude or OpenAI to solve real problems, and you'll be expected to handle model behaviour reliably in production, not just use AI to go faster Direct roadmap ownership: no dedicated PM means you and the team define priorities, your judgment shapes what gets built next Close feedback loop: AML/AFC ops teams proactively raise needs and respond quickly to what you ship. Lead time reduction, prediction confidence, and agent throughput are the metrics that tell you it's working ➡️ Your future team You'll join a team of 5 engineers within Qonto's Financial Crime Compliance (FCC) domain, alongside Ioannis (Tech Lead) and a mix of Senior/Staff Backend Engineers and Machine Learning Engineers. You'll be part of a 190-strong backend engineering community within a 500+ Product Engineering department. One important clarification: this team does not build fraud detection engines or KYC/KYB rule engines. Those exist elsewhere at Qonto. This team builds the automation layer on top, turning model outputs into decisions that help compliance agents respond faster. It's a backend role at the intersection of AI integration and regulated-industry operations. ➡️ About you AI integration in production: You've shipped systems where AI (Claude, OpenAI, or open-source) is a core functional component, not a coding assistant, but the product itself. Strong backend foundation: Solid experience with large-scale web application architecture and real production constraints + Ideally experience in Python. Sound architectural judgment: You make confident system design decisions independently and can articulate the trade-offs. Product instinct without a PM: You're comfortable owning the full cycle: scoping, prioritizing, shipping, success metrics