This role pays less than
65%
of similar roles. Most pay
$205,000–$290,250
— the shaded band above.
At the midpoint, this role pays about
$223k
versus about
$248k
for comparable roles.
Based on 240 similar postings.
Employer
About Johnson & Johnson
Johnson & Johnson is a multinational corporation operating in three main segments: consumer health products, pharmaceuticals, and medical devices, known for brands like Tylenol, Band-Aid, and Janssen. Industry: Pharmaceuticals & Medical Devices
Johnson & Johnson currently has
46 open roles
on FindRole.
Listed pay typically runs
$117,000–$201,250
across 42 roles with salary data.
Director, World Model & Agentic Learning joins the Data, Data Science & AI organization to lead a specialized team within the Generative AI group. This leadership role focuses on building an enterprise world model and agentic-learning capabilities for a reusable R&D agentic AI platform. The successful candidate will design technical architectures for knowledge representation, ensuring agents reason against accumulated domain understanding rather than re-deriving information from raw sources. Key responsibilities include developing mechanisms for continuous learning through expert corrections and in-context refinement to improve system performance over time. The role requires expertise in large language models, retrieval-augmented generation, agentic frameworks, and knowledge representation. This position addresses the challenge of creating durable, product-agnostic capabilities where systems must maintain high confidence, remain auditable, and provide consistent reasoning within complex, high-stakes research and development environments.
LLMs
Agent Frameworks
RAG
Vector Databases
Python
Prompt Engineering
Machine Learning
Deep Learning
Cloud-native Development
APIs
Data Science
Statistical Analysis
Time Series Analysis
Data Visualization
Observability
Generative AI
Large Language Models
Agentic AI
MLOps
AIOps
Data Engineering
Snowflake
Databricks
Azure
AWS
Cloud Infrastructure
Data Architecture
Semantic Modeling
Common Data Model
Data Governance
Generative AI
Natural Language Processing
Large Language Models
Python
Pytorch
Hugging Face
LangChain
Lightning
AWS
VectorDBs
Machine Learning
Relational Databases
Scala
R
Computer Vision
Speech Recognition
Data Analytics
AI
Machine Learning
Reinforcement Learning
Model Training
AI-for-systems
hardware–software stack
Compiler
Inference
Research Prototyping
Training Pipelines
Performance Optimization