Sr Director/scientific Fellow, AI Safety, R&d Data Science and Digital Health

Johnson & Johnson Johnson & Johnson · Pharma · Titusville, NJ +5

Seeking a highly technical leader in AI safety for R&D Data Science & Digital Health. This role is responsible for embedding AI safety, robustness, and observability into the design, evaluation, and deployment of advanced AI systems across the DSDH portfolio and R&D use cases, including foundation models, generative AI, and autonomous agentic systems. The role involves shaping strategy, conducting research, providing technical guidance in regulated environments, influencing policy, and driving external publications.

What you'd actually do

  1. Shape DSDH and IM R&D strategy for safe and trustworthy AI by defining multi-year research priorities, capability roadmaps, and investment recommendations for AI safety across discovery, development, clinical, and regulatory workflows.
  2. Research, embed and implement AI safety-by-design principles into the development of foundation models, AI and generative AI applications, and agentic systems across R&D use cases.
  3. Provide technical leadership for AI safety in regulated environment, covering use cases, e.g. regulatory documentation for AI-enabled R&D processes and submissions, autonomous agents in GxP environments, etc..
  4. Drive J&J innovation in the field, leading to high visibility publications in top-tier AI conferences and journals, patents around AI safety in generative AI, reasoning, multi-agent systems, etc.

Skills

Required

  • AI safety research and development
  • technical leadership in AI safety
  • experience with foundation models, generative AI, and agentic systems
  • understanding of AI safety principles and implementation
  • experience in regulated environments (GxP, regulatory affairs)
  • ability to shape strategy and define research priorities
  • strong publication record in top-tier AI conferences and journals
  • experience with model evaluation and risk assessment

Nice to have

  • experience with policy influence and setting
  • business case development for AI capabilities
  • external ambassadorship and speaking engagements

What the JD emphasized

  • AI safety
  • agentic systems
  • regulated environment
  • safety principles
  • safety-by-design
  • safety-focused models and evaluations
  • safe GenAI
  • autonomous agents

Other signals

  • embedding AI safety, robustness, and observability into the design, evaluation, and deployment of advanced AI systems
  • foundation and predictive AI models, generative AI, and autonomous agentic systems
  • safe, trustworthy, and fit-for-purpose as AI capability and autonomy scale
  • AI safety in regulated environment