Experteer Overview In this role, you lead end-to-end AI capabilities within a large, multi-service environment, shaping how AI functions integrate, are evaluated, and managed for security and compliance.

You drive technical direction, base go/no-go decisions on evidence, and influence multiple teams without direct reports.

You will design scalable AI solutions that handle real-world advisories, package metadata, and third-party code, while ensuring auditable, cost-aware decisions.

This is a hands-on, impact-driven position at enterprise scale with a strong focus on risk management and secure deployment.

Compensaciones / Incentivos • Write use-case specifications for each AI function, defining inputs, behavior, success criteria, failure modes, and human decision points; determine automation vs. assist vs. approval with capability owners.

- Design and run evaluation plans including golden datasets, correctness/safety metrics, offline/online evaluation, and drift monitoring in production.
- Own acceptance gates and make go/no-go decisions across build, pilot, limited, and general availability; escalate unresolved disagreements through governance.
- Define model placement, data flows, human-in-the-loop points, and audit-retained evidence; review all AI-related integration designs.
- Own the AI threat model and test controls against prompt injection, data leakage, unsafe actions, and model supply-chain risk; lead response to misbehaving AI functions.
- Coordinate with external AI providers on quality requirements, evaluation obligations, model-change notifications,



and defect handling.
- Set engineering standards for AI use, including tools, data handling, review of AI-generated code, provenance, licenses, and secrets.
- Mentor engineers working on AI functions and cultivate evaluation skills across teams; stay hands-on by building datasets, running evaluations, and reviewing code whenever needed.

Responsabilidades • 10+ years in software engineering with production shipping of LLM-based or ML-based features.

- Experience in AI evaluation: correctness and safety metrics, offline/online evaluation, drift monitoring, and evidence-based launch decisions.
- Proficient in designing and reviewing service integrations, data flows, human-in-the-loop, and evidence retention.
- AI security expertise: threat modeling and controls against prompt injection, data exfiltration, and unsafe tool use.
- Vulnerability management knowledge: advisories, CVEs, SBOMs, and remediation processes.
- Strong specification skills: writing acceptance criteria for engineers and suppliers.
- Hands-on coding in Python, Go, Java, or Rust.
- Technical leadership without formal authority; mentoring and ability to push back on unverified evidence.
- Excellent communication to explain risk to executives and constraints to developers, in English.

Requisitos principales • Hybrid work model • Belonging and inclusive culture • Continuous learning and development opportunities • Share matching program • Flexible benefits for you and family • Recognition of LinkedIn Top Companies to Work For ****

📌 Staff Ai Engineer (M/F/D) (Madrid)
🏢 Siemens
📍 Madrid