Director, World Model & Agentic Learning

Role: Director, World Model & Agentic Learning within Johnson & Johnson's Generative AI organization, leading the development of enterprise AI systems for R&D. Responsibilities: design and oversee mechanisms for knowledge representation, reasoning, and continual learning that improve decision-making over time; partner with scientific and domain experts to ensure authoritative judgment; lead a team of 4–8 AI scientists; collaborate with evaluation, platform, and data teams to ensure system accountability, transparency, and integration across workflows. Requirements: minimum 8 years in AI/ML system design and deployment; expertise with large language models, retrieval-augmented generation, knowledge representation, and continual learning; proven experience leading technical teams, setting architecture, and partnering with high-stakes sectors like healthcare or life sciences. Preferred: PhD in relevant fields; experience with knowledge graphs, structured memory, and auditable AI systems; published work in continual learning and agentic AI; familiarity with regulated/high-stakes environments. HighValue: focus on knowledge accumulation, memory systems, and decision quality in scientific R&D; leadership in AI for healthcare or pharma; hybrid work locations in the U.S.; collaborative relationships across scientific, technical, and evaluation teams.