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 |
|---|---|---|
| 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 |
| 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 |
| Postdoctoral Researcher Video team Postdoctoral researcher to join the Video Understanding team, focusing on designing, implementing, and evaluating state-of-the-art AI/ML methods for frame-level and video-level understanding across diverse medical modalities. The role involves developing robust uncertainty models and multi-modal architectures to extract reliable insights from clinical data, collaborating with clinicians and engineers to translate algorithms into high-impact tools for clinical trial efficacy and workflows. | Post-trainAgent | 8 |
| 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 on cofolding models for In-Silico Drug Discovery Postdoctoral researcher focused on developing and fine-tuning co-folding models for in-silico drug discovery, involving dataset curation, model evaluation, and integration into discovery workflows within a healthcare/biotech domain. | Post-train | 7 |
| Postdoctoral Scholar Computational Chemistry This role focuses on developing and employing quantum chemical simulations and machine learning workflows to advance the development of small molecule medicines and therapies. The primary focus is on estimating synthetic outcomes and assessing chemical degradation pathways in silico, with a secondary focus on developing and validating ML components for reaction outcome estimations. | DataPost-train | 7 |
| Postdoctoral Scientist Data Science AI/ML & DH Postdoctoral Scientist role focused on developing digital biomarkers and AI algorithms for digital endpoint development using wearable sensor data within Johnson & Johnson's healthcare research division. | DataPost-train | 7 |