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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff Software Engineer, AI Agents (Python) - **Company:** Qonto - **Location:** Berlin, Germany - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Databases, Python (Programming Language), Machine Learning, Systems Integration, Backend, Agentic-AI, Virtual Agents - **Published:** October 12, 2026 - **Apply:** https://www.adzuna.de/details/5922443917 ## About the Role * Production AI experience: You have shipped an AI agent or agentic workflow used by real users and can explain its orchestration, tool use, state, structured outputs, evaluation, retries, and failure modes * Strong backend engineering: You bring solid system-design fundamentals across architecture, APIs, databases, integrations, reliability, observability, maintainability, and scalability * Staff-level autonomy and judgement: You make sound decisions independently, communicate trade-offs clearly, and know when to optimise for speed and when quality is non-negotiable * Product and stakeholder thinking: You can turn ambiguous operational pain into a valuable solution, challenge assumptions, prioritise scope, and define success without relying on a PM * End-to-end ownership: You are willing to discover, build, ship, operate, maintain, and continuously improve the systems you create * Learning agility: You are curious about AFC and regulated workflows and can ramp up quickly in a complex domain; prior fintech or compliance experience is helpful, not required * Pragmatic technology choices: Python experience and familiarity with current model providers or agent frameworks are useful, but transferable production principles matter more than expertise in a specific language or vendor ## Description Join us as a Staff Applied AI Engineer, Backend to build production systems in which AI is a core runtime capability. You'll help Qonto's Anti-Financial Crime teams investigate cases faster and with greater confidence by turning complex operational workflows into dependable, measurable tools. ️ As a Staff Applied AI Engineer you will * Build production AI systems: Design and ship agentic tools and AI-powered workflows that gather context from multiple internal systems, orchestrate models and tools, parse structured outputs, and handle uncertainty and failure safely * Own projects end to end: Lead discovery with AFC stakeholders, shape the solution, make architectural decisions, implement and launch it, then operate, maintain, and improve it in production * Design robust backend foundations: Build reliable, maintainable, and extensible services, APIs, databases, and integrations around evolving AI models and tooling * Make AI behaviour measurable: Define evaluation approaches, observability, fallbacks, and human-review mechanisms; monitor output quality, acceptance and edit rates, throughput, and operational impact * Deliver measurable operational value: Reduce investigation lead time and expand automation across AFC workflows through pragmatic, incremental delivery * Shape the team's technical direction: Lead design discussions, anticipate risks, balance speed with quality, and help raise the team's capability in production agentic systems ️ What you can expect * AI at the heart of the system: This is not a conventional backend role using AI only as a coding assistant, nor an ML research role. You'll build real products where model behaviour, orchestration, evaluation, and failure handling are production concerns * High autonomy: There is no dedicated Product Manager. Engineers work directly with AFC stakeholders and own the path from an ambiguous operational need to a measurable production outcome * Lean, iterative delivery: The team uses a daily 15-minute blocker sync, bi-weekly 1:1s, and lightweight tracking, leaving engineers focused on building and solving problems * A close user feedback loop: You'll collaborate directly with operational teams and measure success through investigation lead-time reduction, output quality, human acceptance and edit rates, adoption, throughput, and resources saved * A complex, meaningful domain: You'll learn how to build safe, scalable AI automation in a regulated environment where reliability and auditability matter ️ Your future team You'll join Qonto's AI Compliance Tooling team within the Financial Crime Compliance domain. The current team brings together Ioannis, the Tech Lead and a hands-on contributor; Staff Backend Engineer Enrique; Staff Machine Learning Engineer Luca; and Senior Backend Engineers Izan and Robson. The team is growing with two additional staff-level hybrid backend/AI hires.