Our client is a fast-growing European fintech company in the business spend management space. We're looking for a Senior Applied AI Engineer to design, build and ship customer-facing AI features end-to-end. Responsibilities Design, build and ship customer-facing AI features end-to-end, including RAG system design (chunking, embedding selection, retrieval, re-ranking) and agentic workflows. Ship external customer-facing LLM-based features into production, with safe production deployment practices. Do hands-on evaluation-pipeline and observability work: drift detection, quality monitoring. Reason independently about retrieval architecture using strong data fluency. Apply real engineering rigor to the Context Development Lifecycle (CDLC): generate, evaluate, distribute and observe the context that powers AI agents. Multiply the output and quality of the squad you join, and share patterns/practice beyond your immediate team so adoption compounds across the organisation. Embed directly into a client squad as a hands-on Individual Contributor.



Requirements: Python (Python-first). RAG system design: chunking, embedding selection, retrieval, re-ranking. Proven experience shipping external customer-facing LLM-based features to production (not prototypes). Hands-on evaluation-pipeline and observability work: drift detection, quality monitoring. Data fluency to reason about retrieval architecture independently. Agent & harness engineering fluency — designing guardrails, context and verification layers for safe, reliable AI‑assisted delivery;
concrete evidence of having built/operated this kind of tooling, not just used it. Comfortable with the client's current daily tools: Claude Code and Git Hub Copilot. Nice-to-Have: Specific tooling such as AWS Bedrock, Open AI APIs, or Langfuse (or comparable eval platforms). Project: Automated claims management platform. #J-18808-Ljbffr

📌 Senior Applied Ai Engineer (España)
🏢 N-iX
📍 España