backend developer for financial crime compliance

Qonto provides a finance workspace for SMEs, with banking at its core and additional financial tools. Its AI Compliance Tooling team builds AI-powered automation and intelligence tools that help human investigators handle financial crime compliance workflows.

• Build and ship production AI systems, agentic tools, and AI-powered workflows that gather context from internal systems, orchestrate models and tools, parse structured outputs, and safely handle uncertainty and failure
• Own projects end to end, from discovery with AFC stakeholders and solution design to architectural decisions, implementation, launch, operation, maintenance, and improvement
• Build reliable, maintainable, and extensible backend services, APIs, databases, and integrations for evolving AI models and tooling
• Define evaluation approaches, observability, fallbacks, and human-review mechanisms; monitor output quality, acceptance and edit rates, throughput, and operational impact
• Reduce investigation lead time and expand automation across AFC workflows through pragmatic, incremental delivery
• Lead design discussions, anticipate risks, balance speed with quality, and help raise the team’s capability in production agentic systems

• Experience shipping an AI agent or agentic workflow used by real users, including orchestration, tool use, state, structured outputs, evaluation, retries, and failure modes
• Strong system-design fundamentals across architecture, APIs, databases, integrations, reliability, observability, maintainability, and scalability
• Ability to make independent decisions, communicate trade-offs clearly, and balance speed with quality
• Ability to turn ambiguous operational needs into valuable solutions, challenge assumptions, prioritise scope, and define success without relying on a Product Manager
• Willingness to discover, build, ship, operate, maintain, and continuously improve systems
• Curiosity about AFC and regulated workflows, with the ability to ramp up quickly in a complex domain
• Будет плюсом: prior fintech or compliance experience, Python experience, familiarity with current model providers or agent frameworks

• The team has no dedicated Product Manager; engineers work directly with AFC stakeholders and own solutions from ambiguous needs through measurable production outcomes
• The team uses a daily 15-minute blocker sync, bi-weekly 1:1s, and lightweight tracking
• Engineers 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
• The role involves building safe, scalable AI automation in a regulated environment where reliability and auditability matter
• The team does not build fraud-detection engines or KYC/KYB rule engines; it consumes upstream signals and builds the AI-powered automation and intelligence layer used by human investigators
• The current system gathers information from 10–15 internal tools and produces a structured compliance analysis for a person to approve or edit, reducing treatment time from approximately 15–20 minutes to about 30 seconds
• Hiring is open to candidates regardless of which hiring-checklist boxes they tick
• By applying, candidates agree that Qonto processes their personal data to assess their application. Data is kept for up to 2 years in the candidate pool
• The hiring process lasts an average of 20 working days
• Qonto does not work with third-party platforms or agencies that request payment from candidates; suspicious messages claiming to be from Qonto should be reported