Johnson & Johnson currently has 73 active AI-related job listings. The majority of these roles, specifically 44%, are in the agents stage. Engineering is the most frequent function for these hires, followed by Product. The company is primarily hiring in the United States. Frequent tech tags include agent_orchestration and model_serving, suggesting a focus on AI system deployment and management. In the last 30 days, Johnson & Johnson posted 104 new AI roles, representing a significant increase of 420% compared to the previous 30-day period.
Currently tracking 49 active AI roles, down 53% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $77k–$283k (avg $144k).
Johnson & Johnson currently has 62 active AI-related roles in our index. The most common open titles are: Principal Scientist, Data Science - DDSAI - Therapeutics Development Supply (4), Data Scientist and Application Developer (2), Lead-Data Automation and Excellence (2), Postdoctoral Data Analytics Computational Sciences (2), Senior Program Manager, R&D (2). Most positions are in Engineering and Product.
Johnson & Johnson's active AI hiring is concentrated in: agents (40%), application (19%), data (18%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Johnson & Johnson is hiring AI talent in: United States (38 roles), Spain (7 roles), Belgium (5 roles), Japan (4 roles).
Job postings at Johnson & Johnson most frequently reference: agent orchestration, model serving, llm observability, fine tuning, rag.
In the past 30 days, Johnson & Johnson has posted 69 new AI-related roles. That is a -37% change versus the prior 30 days (109 → 69).
| Title | Stage | AI score |
|---|---|---|
| Director, Data Analytics - EMEA Director of Analytics role focused on building and scaling AI-infused analytics capabilities to drive fact-based decision-making and measurable business impact within the MedTech Supply Chain Digital & Data organization. The role involves defining analytics strategy, leading the development of scalable analytics solutions (including AI-enabled insight products), partnering with senior leaders, driving adoption, ensuring governance, transforming capabilities, and leading analytics teams. | ShipPost-train | 7 |
| Principle Optimization Engineer This Principal Optimization Engineer role focuses on designing, developing, and deploying optimization and simulation capabilities for complex supply chain problems. It involves crafting algorithms, piloting solutions, and scaling them across the enterprise. The role will incorporate AI/ML techniques, including Generative AI and Agentic AI, to enhance decision-support capabilities. Collaboration with data scientists, data engineers, and product management is key, as is driving innovation in supply chain methods. |
| AgentData |
| 7 |