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 |
|---|---|---|
| Senior Scientist, AI Applications - R&D Immunology Data Science & Digital Health Senior Scientist role focused on developing and delivering AI/ML scientific applications in Immunology R&D, specifically working with LLMs and advanced data science techniques to accelerate drug discovery. Key focus areas include multimodal reasoning, agent robustness, memory architectures, and uncertainty quantification. The role involves hands-on technical delivery, translating business opportunities into research plans, and contributing to the broader AI strategy. | Agent | 9 |
| Senior Scientist – AI Agent Systems for Drug Development Seeking a Senior Scientist to develop autonomous AI agent systems for drug discovery and development, focusing on multimodal reasoning, agent robustness, memory, and motivation using LLMs and large datasets. | Agent |
| 9 |
| Sr Director/Scientific Fellow, AI Safety, R&D Data Science and Digital Health Seeking a Scientific Fellow to lead AI safety initiatives within R&D Data Science & Digital Health. This role focuses on embedding safety, robustness, and observability into advanced AI systems, including foundation models, generative AI, and agentic systems, across discovery, development, clinical, and regulatory workflows. The position involves hands-on technical leadership, research, policy influence, and external engagement to ensure AI systems are safe, trustworthy, and fit-for-purpose in a regulated healthcare environment. | AgentPost-train | 9 |
| Sr Director/Scientific Fellow, AI Safety, R&D Data Science and Digital Health Seeking a highly technical leader in AI safety for R&D Data Science & Digital Health. This role is responsible for embedding AI safety, robustness, and observability into the design, evaluation, and deployment of advanced AI systems across the DSDH portfolio and R&D use cases, including foundation models, generative AI, and autonomous agentic systems. The role involves shaping strategy, conducting research, providing technical guidance in regulated environments, influencing policy, and driving external publications. | AgentPost-train | 9 |
| Senior Scientist, AI Applications - R&D Oncology Senior Scientist role focused on developing and delivering AI/ML scientific applications for oncology drug discovery and development. The role involves working with LLMs, multimodal reasoning, agent memory architectures, and uncertainty quantification to accelerate research. Key responsibilities include hands-on technical delivery, prototyping, evaluation, and defining best practices for AI applications. | Agent | 9 |
| Associate Director, R&D Neuroscience Data, Data Science & AI - Ophthalmology Associate Director role focused on leveraging AI/ML, computer vision, and generative AI with multimodal data (ophthalmic imaging, clinical, RWE) to accelerate drug discovery and development in ophthalmology, identify digital biomarkers, and stratify patients. The role involves developing and validating digital endpoints and integrating RWE, with a strong emphasis on collaboration and regulatory engagement. | AgentData | 8 |
| Associate Director, R&D Neuroscience Data, Data Science & AI – Ophthalmology Associate Director role focused on leveraging multimodal data, digital health, computer vision, AI, and RWE to accelerate drug discovery and development in ophthalmology. The role involves developing and applying advanced AI/ML methods, particularly computer vision for ophthalmic imaging, creating digital endpoints, integrating RWE, and applying generative AI to multimodal datasets for disease understanding and patient stratification. | AgentData | 8 |
| Director, R&D Neuroscience Data Science & Digital Health – Ophthalmology Director role focused on leveraging AI/ML, computer vision, and digital health technologies to accelerate drug discovery and development in ophthalmology. This involves analyzing multimodal data, developing digital endpoints, integrating real-world evidence, and applying generative AI for insights. The role emphasizes collaboration with cross-functional teams and external partners to enhance clinical trial execution and patient care. | AgentData | 8 |
| Senior Director, R&D Data Science & Digital Health – Ophthalmology Senior Director to lead data science and digital health strategy for ophthalmology, leveraging multiomics, digital health, AI/ML, and RWE to accelerate drug discovery and development. The role involves defining strategy, driving application of multiomics and integrative analytics, leading development of digital tools and endpoints, championing AI/ML for patient stratification and disease modeling, integrating RWE, building collaborations, and managing a team. | AgentData | 7 |