Experteer Overview

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In this role you drive safe, trustworthy agentic AI for pharmaceutical Ru0026amp;D within Johnson u0026amp; Johnson’s Data, Data Science u0026amp; AI group in Madrid or Barcelona. You define provable controls, adversarial assurance, and safety-native architectures to ensure AI systems are safe by design for regulated workflows. You will collaborate with cross-functional teams to translate safety requirements into scalable controls and prototypes, shaping the GenAI Platform and contributing to scientific and regulatory proof. This is an impactful, hands-on role at the frontier of AI safety in life sciences.

Compensaciones / Ventajas
• Design machine-readable control policies governing agent actions, tool use, data access, and information flow across agentic workflows.
• Implement deterministic policy enforcement with auditable decisions and defined human-approval paths.
• Enable domain and system owners to author,



test, and maintain controls via accessible policy interfaces.
• Develop continuous red-teaming methods for agentic AI, integrating threat models with Ru0026D failure modes.
• Embed adversarial evaluation into the GenAI Platform to test models, agents, tools, and end-to-end workflows.
• Define evaluation protocols and evidence thresholds to distinguish safety properties from unverified claims.
• Research and prototype safety-native architectures that constrain agent behavior with layered controls.
• Evaluate pre-training data interventions and post-training methods for regulated scientific use cases.
• Translate scientific, quality, privacy, and regulatory requirements into testable system specifications for models, agents, tools, and runtime controls.
• Define accountability measures and ensure control decisions are traceable and reconstructable as audit evidence. xghoner
• Partner with

📌 Senior Scientist (Madrid)
🏢 Johnson u0026 Johnson
📍 Madrid