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 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.
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 |
|---|---|---|
| Postdoctoral Data Analytics Computational Sciences Postdoctoral researcher for application of advanced AI/ML methods to microscopic images of clinical and preclinical histopathology. Focus on application and refinement of deep learning algorithms to quantitate histopathology, and implementation of novel state-of-the-art techniques. Improve understanding of cellular organization and tissue structure to enhance clinical trial efficacy and efficiency. | Post-trainServe | 9 |
| Sr. Principal Scientist, Spatial Omics Senior Principal Scientist role focused on applying and developing AI/ML frameworks for multimodal biological datasets, including spatial omics, genomics, transcriptomics, proteomics, and metabolomics. The role involves designing and building ML-based and agent-based models to simulate biological dynamics, integrating mechanistic models with AI, and contributing to the data and modeling architecture for large-scale ML training. The position emphasizes scientific leadership and innovation in computational biology for therapeutic discovery. |
| DataAgent |
| 9 |
| 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 |
| 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 |
| Director, R&D Neuroscience Data, Data Science & Artificial Intelligence - Ophthalmology 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, enhance clinical trial execution, and develop digital biomarkers and endpoints. The role involves advanced statistical modeling, RWE integration, and collaboration with cross-functional teams and external partners. The primary output is a patient-centric AI-driven product/solution for ophthalmic diseases. | ShipData | 8 |
| Post Doctoral Researcher, Evaluation & Standards in Clinical Operations Postdoctoral researcher to develop evaluation frameworks, rubrics, and quality systems for generative AI agents used in clinical operations and global development workflows. The role involves defining quality dimensions, designing human evaluation protocols, building benchmark datasets, and partnering with AI engineering teams in a regulated pharmaceutical environment. | Eval GateAgent | 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 Scientist Omics - IMM Senior Scientist role focused on analyzing large-scale clinical, genetic, omics, and cell phenotype data to identify and evaluate drug targets for the Immunology therapeutic area. The role involves constructing analytic frameworks, applying statistical modeling and AI/ML methods, and using NLP to annotate targets and biomarkers. This is a research-focused position within healthcare, utilizing AI/ML for drug discovery and development. | Data | 7 |
| Postdoctoral Scholar, AI/ML for drug metabolite prediction and LC-MS analytical chemistry This role focuses on developing and evaluating AI/ML models for drug metabolite prediction, pharmacokinetics, and molecular properties within a healthcare/drug discovery context. It involves fundamental research using internal datasets, developing explainable AI tools with uncertainty estimation and active learning, and publishing findings. The role is primarily research-oriented, building and evaluating deep learning methods for analytical instrumentation and drug discovery processes. | Post-train | 7 |
| PostDoc Neuroscience Computational Biology Postdoctoral Scientist role in neuroscience computational biology at Johnson & Johnson, focusing on analyzing large-scale omics data to understand neuropsychiatric and neurodegenerative disorders using AI-enabled, data-driven drug discovery approaches. Responsibilities include novel target identification, genetics association analysis, proteome-wide multi-task learning, and patient stratification. The role involves developing computational pipelines, analyzing multi-omics data, and publishing findings. | DataPost-train | 7 |
| Postdoctoral Scientist Data Science AI/ML & DH Postdoctoral Scientist role focused on developing digital biomarkers and AI/ML algorithms for digital endpoint development using wearable sensor data within Johnson & Johnson's Innovative Medicine Research & Development division. Responsibilities include data analysis, feature extraction, model building, pipeline development, and collaboration with cross-functional teams, with an emphasis on scientific publication. | Post-trainData | 7 |
| Director, Data Science and Digital Health - Hematology, Oncology Director level role focused on applying Data Science and AI/ML to support early-stage Hematology Oncology drug development at Johnson & Johnson. Responsibilities include identifying and delivering Data Science capabilities, applying advanced analytic methodologies to high-dimensional data like real-world evidence, and contributing to data-driven decision-making in R&D. | Data | 7 |
| 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 |