Director, World Model & Agentic Learning

Scorpion Therapeutics; New Jersey; Hybrid; USD 180,000 - 300,000; Full time

Job summary

Johnson & Johnson is seeking a senior leader to head the AI science team, focusing on an enterprise world model and agentic-learning capabilities. The role emphasizes knowledge accumulation, reasoning, self-assessment, and real-world feedback-driven improvement.

Responsibilities include guiding technical direction, embedding expert judgment, and managing a team of AI scientists in a hybrid US setting with locations like Cambridge, MA and Titusville, NJ.

Qualifications

• 8+ years in industry AI/ML system development with hands-on LLMs.
• Experience in knowledge representation and continual learning.

Responsibilities

• Set technical direction for AI science initiatives.
• Build mechanisms for knowledge representation, confidence estimation, and reasoning.
• Partner with scientists to embed expert judgment into AI systems.
• Lead a team of 4-8 AI scientists.
• Establish a culture of rigor and accountability.
• Collaborate across R&D, data and AI evaluation teams.

Skills

Team leadership

AI/ML systems

Knowledge graphs

Continual learning

Education

PhD preferred

Job description

Role

Lead the AI science team focused on developing J&J's enterprise world model and agentic-learning capabilities within the Generative AI organization. Primary objectives include designing systems for knowledge accumulation, reasoning, self-assessment, and continuous improvement from real-world operation and expert feedback.

Responsibilities

• setting technical direction
• building mechanisms for knowledge representation, confidence estimation, and reasoning
• partnering with scientists and domain experts to embed expert judgment into AI systems
• leading a team of 4-8 AI scientists
• establishing a culture of rigor and accountability
• collaborating across R&D, data, and AI evaluation functions

Qualifications

• minimum 8 years in industry AI/ML system development, with hands-on experience in large language models, knowledge representation, and systems emphasizing continual learning and knowledge accumulation

Preferred

• advanced degree (PhD)
• experience in regulated environments such as life sciences or healthcare
• expertise in knowledge graphs or explicit knowledge systems

High Value

• focus on knowledge-based reasoning, continual learning, agentic AI, and application within life sciences or healthcare R&D

Work setup

hybrid locations in the US, including Cambridge, MA; La Jolla, CA; Titusville, NJ; or Spring House, PA.