Director, World Model & Agentic Learning (AI)

Location: Hybrid position at one of the following U.S. offices: New Brunswick, NJ; Titusville, NJ; Spring House, PA; or Cambridge, MA.

Base pay: $164,000–$282,900 per year.

Company

Johnson & Johnson develops healthcare, pharmaceutical, and MedTech solutions, including innovative treatments and technology for complex diseases.

What you will do

• Lead the AI science team building an enterprise world model and agentic-learning capability for the R&D agentic AI platform.
• Design representations of accumulated domain knowledge, including confidence, boundaries, gaps, contradictions, provenance, and queryable grounding.
• Develop learning mechanisms based on expert corrections, operational outcomes, active learning, memory-based learning, and in-context refinement.
• Partner with scientists and domain experts to apply expert judgment consistently across regulated and high-stakes workflows.
• Define and demonstrate accountability through auditable conclusions, reconstructable decisions, and rigorous evaluation of decision-quality improvement.
• Recruit, develop, and lead a team of 4–8 AI scientists while setting and defending the technical architecture.

Requirements

• At least 8 years of post-academic industry experience building and shipping AI/ML systems, including significant technical architecture ownership.
• Hands-on expertise with large language models, retrieval-augmented generation, agentic frameworks, and knowledge representation.
• Experience designing systems where knowledge accumulation, memory, or continual learning is the central technical challenge.
• Experience building systems that improve through real-world operation and expert feedback.
• Strong people leadership experience, including recruiting and leading technical or scientific teams in a matrixed organization.
• Ability to work in a hybrid arrangement from one of the specified U.S. offices.

Nice to have

• Advanced degree, preferably a PhD, in computer science, AI/ML, applied mathematics, computational science, or a related discipline.
• Experience in life sciences, healthcare, drug discovery, pharmaceutical R&D, or another regulated or high-stakes domain.
• Experience with knowledge graphs, ontologies, structured memory, auditable AI systems, or human-in-the-loop AI.
• Publications or recognized contributions in continual learning, agentic systems, or knowledge representation.
• Experience building reusable frameworks and defining interfaces between knowledge or memory substrates and reasoning agents.

Culture & Benefits

• Inclusive work environment guided by the company’s Credo and equal-opportunity principles.
• Annual vacation, sick time, holidays, personal and family time, parental leave, bereavement leave, caregiver leave, volunteer leave, and military spouse time off.
• Eligibility for a consolidated retirement plan, pension, 401(k) savings plan, and long-term incentive program.
• Collaboration with technology, data, AI evaluation, regulatory, scientific, and external academic and industry partners.