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.

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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 GitHub Copilot.

Nice-to-Have:

Specific tooling such as AWS Bedrock, OpenAI APIs, or Langfuse (or comparable eval platforms). xugodme

Project: Automated claims management platform.

📌 Senior Applied AI Engineer (#5633) (España)
🏢 N-iX
📍 España