Director, World Model & Agentic Learning

Role: Lead the AI science team within Johnson & Johnson's Generative AI organization, focusing on developing enterprise-level world models and agentic learning capabilities for R&D applications. Responsibilities: design and implement systems for knowledge accumulation, reasoning, confidence estimation, and continual learning; partner with domain experts; ensure system transparency, accountability, and continual improvement from operational data; build and lead a team of 4–8 AI scientists; collaborate across scientific and technological functions. Requirements: minimum 8 years industry experience in AI/ML, with expertise in large language models, knowledge representation, and systems emphasizing memory and continual learning. Strong leadership and communication skills are essential. Preferred: advanced degree (PhD) in relevant fields, experience with knowledge graphs, life sciences or regulated environments, and recognized contributions in agentic AI or continual learning. High-value: focus on scientific domains, knowledge-driven reasoning, non-retraining learning mechanisms, and building auditable, high-stakes AI systems. Work setup: hybrid in U.S. offices (e.g., NJ, PA, MA). The role interfaces with R&D, regulatory, data platforms, and external partners, emphasizing scientific rigor, technical architecture, and scalable AI platform development.