Director, World Model & Agentic Learning

Role: Lead the AI science team responsible for developing Johnson & Johnson's enterprise world model and agentic learning capabilities within the Generative AI organization. Main objectives include designing systems for knowledge accumulation, reasoning, and continuous learning that improve from operation and expert feedback. Responsibilities involve devising representation mechanisms, confidence modeling, and ensuring knowledge transfer across workflows; partnering with scientists and domain experts; establishing system accountability and auditability; and leading a team of 4–8 AI scientists. Qualifications: minimum 8 years industry experience in AI/ML, with deep expertise in large language models, knowledge representation, and systems for continual learning; proven leadership in building scalable, knowledge-focused AI systems; strong communication skills for cross-functional alignment. Preferred: PhD in a related field; experience in regulated environments like healthcare or life sciences; familiarity with knowledge graphs, ontologies, and human-in-the-loop AI; publication record in relevant AI domains. Biopharma specifics include applying these AI capabilities to R&D workflows, collaborating with scientific teams, and supporting decision-making in high-stakes, regulated settings. Location: hybrid work at U.S. offices in New Brunswick, Titusville, Spring House, or Cambridge. The role reports to the Head of Generative AI and involves collaboration with platform, evaluation, data, and scientific teams.