Staff Software Engineer, AI Agents (Python)
New
Q
QontoFinancial crime compliance
France, Germany, Spain, or Italy — remote within these hiring locations.Full-TimeStaff
Salary not disclosed
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Job Details
- Required Skills
- PythonRESTful APIs
Requirements
- Have shipped an AI agent or agentic workflow used by real users.
- Be able to explain agent orchestration, tool use, state, structured outputs, evaluation, retries, and failure modes.
- Bring strong backend engineering and system-design fundamentals across architecture, APIs, databases, and integrations.
- Understand reliability, observability, maintainability, and scalability.
- Make sound decisions independently and communicate trade-offs clearly.
- Turn ambiguous operational needs into valuable solutions, challenge assumptions, prioritise scope, and define success without relying on a Product Manager.
- Be willing to discover, build, ship, operate, maintain, and continuously improve systems.
- Be curious about Anti-Financial Crime and regulated workflows, with the ability to ramp up quickly in a complex domain.
- Python experience and familiarity with current model providers or agent frameworks are useful; transferable production principles matter more than expertise in a specific language or vendor.
- Prior fintech or compliance experience is helpful, but not required.
Responsibilities
- Design and ship agentic tools and AI-powered workflows that gather context from internal systems, orchestrate models and tools, parse structured outputs, and handle uncertainty and failure safely.
- Lead discovery with Anti-Financial Crime stakeholders, shape solutions, make architectural decisions, implement and launch projects, and operate and improve them in production.
- Build reliable, maintainable, and extensible services, APIs, databases, and integrations around evolving AI models and tooling.
- Define evaluation approaches, observability, fallbacks, and human-review mechanisms for AI behavior.
- Monitor output quality, acceptance and edit rates, throughput, and operational impact.
- Reduce investigation lead time and expand automation across Anti-Financial Crime workflows through incremental delivery.
- Lead design discussions, anticipate risks, balance speed with quality, and help raise the team’s capability in production agentic systems.
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