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 2026

📌 Staff AI Engineer (m/f/d) (Madrid)
🏢 Siemens
📍 Madrid