Qonto · Paris, France
Skills: Python, AWS
Join us as an AI Engineer in our AI Products team to make sure the AI agents we ship are as reliable as they are fast to build. You'll design the evals, observability and tooling that keep agent quality high in a regulated bank.
➡️ What you'll do ---------------------
Build agents: You'll develop agents that take real actions for customers. Match rigor to risk: You'll size evaluation to the stakes, because an agent making transfers is not a PR bot. Own evaluation of every feature: You'll make sure every new agent capability comes with the right evaluation strategy, defining what needs to be tested offline and validated online, based on business requirements, expected outcomes and risk. Observe agents in production: You'll build the monitoring strategy that makes agent behaviour visible, tracks performance against business objectives and flags issues early. Scale it as a platform: You'll turn our tools, evaluation practices and monitoring capabilities into a self-service platform that lets other teams build, evaluate and operate their own agents.
➡️ What we're looking for -----------------------------
Evaluation mindset: You've evaluated models or LLM systems and know what makes a test misleading. Strong ML foundations: You understand the ML lifecycle, from training and iteration to evaluation and monitoring, and core concepts such as overfitting, generalization and cross-validation. LLM and agentic systems knowledge: You understand the fundamentals of LLMs (particularly the Transformer architecture) and the building blocks of agentic systems. You know how to optimize an agent's harness (prompts, tools, hooks and orchestration) to improve its reliability and performance. Builder instinct and backend comfort: You've built and shipped something used by real users, whether professionally, during an internship or as a side project. You're comfortable reading and writing backend code, working with APIs and integrating systems. AI-nativ …truncated… ➡️ What we can offer you ---…
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