At Johnson it must be a property of how these systems are built.
You will define how pharmaceutical R set the scientific direction for a small cross-functional team and represent the work externally through publications and standards contributions.
What This Role Is Not * Not frontier model development.
We are not pre-training foundation models at scale.
The research question is how alignment and architecture should be adapted so that the models and platforms available to us are safe for pharmaceutical R you are not the second-line reviewer who signs off on it.
* Not a guardrail-prompt role.
Safety here is architectural and enforcement is deterministic.
A system prompt asking a model to behave is not a control.
* Not an enterprise-wide rollout role at hire.
Scope begins with selected R you design independent behavioral and system-level tests.
* You have applied policy-as-code, information-flow control, formal methods, or provenance systems to govern agent actions, tool use, and data access-and understand that policy exceptions are a primary attack surface.
* You have adversarially evaluated deployed AI systems, reproduced failure modes, and reported findings independently of the teams that built them.
* You can detect evaluation leakage, overfitting, weak baselines, and test-set artifacts before they are mistaken for genuine safety performance.
* You treat unusable safeguards as a safety failure because controls that disrupt scientific work will be bypassed or disabled.
* You want to advance AI safety where model and agent failures can affect scientific evidence, regulatory decisions, and patient outcomes.
Key Qualifications * PhD in computer science, AI/ML, applied mathematics, or a closely related technical field-required.
* At least one year of post-PhD research or industry experience developing and deploying AI/ML, autonomous-agent, or security-critical systems.
* Deep, hands-on expertise in agentic AI, including foundation models, retrieval-augmented generation, tool orchestration, memory,



planning, multi-agent frameworks, and associated failure modes.
* Demonstrated research or applied expertise in AI safety and alignment, such as supervised fine-tuning, preference optimization, safety tuning, adversarial evaluation, interpretability, or scalable oversight, including their limits in specialized domains.
* Demonstrated expertise in at least one of the following: policy-as-code and authorization; adversarial machine learning and AI red teaming; information-flow or data-access control; provenance and lineage; formal specification or verification.
* Strong AI engineering skills, including prototyping evaluation and control methods, building reproducible experiments, and writing production-ready code.
* Excellent written and verbal communication, with the ability to present technically defensible AI safety arguments to scientific, engineering, and executive stakeholders.
* Scientific rigor in characterizing model and agent behavior, including uncertainty, limitations, failure conditions, and the strength of supporting evidence.
Preferred Qualifications * Published or recognized work in top-tier journals/conferences in AI safety, alignment, adversarial ML, verified systems, information-flow control, or human oversight.
* Experience adapting foundation models to scientific domains and testing whether safety properties persist.
* Hands-on experience with policy engines, authorization languages, or formal policy specifications.
* Familiarity with AI threat and governance frameworks, including MITRE ATLAS, OWASP LLM guidance, NIST AI RMF, ISO/IEC *, or the EU AI Act.
* Experience with data classification, de-identification, and privacy-preserving ML, including their limitations.
* Experience deploying AI in life sciences or another regulated, high-stakes domain.
* Familiarity with GxP, data integrity, and validation of AI-enabled computerized systems.Experience evaluating third-party AI safety, evaluation, or control technologies.
* Experience building reusable AI safety capabilities adopted across teams.
Johnson

📌 Senior Scientist (España)
🏢 Johnson & Johnson
📍 España