JPMorgan Chase has 448 active AI-related job listings. The majority of these roles, 55%, are focused on agents, with application roles making up another 17%. The dominant function for these positions is Engineering, with a significant number of roles also in Product. The company is primarily hiring in the United States, followed by the United Kingdom and India. Frequent tech tags include agent_orchestration, llm_observability, and model_serving. In the last 30 days, JPMorgan Chase posted 275 new AI roles, representing a 76% increase compared to the previous 30-day period.
Currently tracking 305 active AI roles, with 1181 new openings in the last 4 weeks. Primary focus: Agent · Engineering. Salary range $153k–$285k (avg $226k).
JPMorgan Chase currently has 445 active AI-related roles in our index. The most common open titles are: Data Scientist [Multiple Positions Available] (7), Lead Software Engineer (6), Applied AI ML-Vice President (4), Applied AI/ML Lead (4), Applied AI ML-Senior Associate (3). Most positions are in Engineering and Product.
JPMorgan Chase's active AI hiring is concentrated in: agents (57%), application (17%), serving infrastructure (9%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
JPMorgan Chase is hiring AI talent in: United States (299 roles), United Kingdom (64 roles), India (56 roles), Singapore (16 roles).
Job postings at JPMorgan Chase most frequently mention: Machine Learning, Agentic Systems, Statistics, Data Science, Large Language Models (LLMs).
In the past 30 days, JPMorgan Chase has posted 178 new AI-related roles. That is a -35% change versus the prior 30 days (274 → 178).
| Title | Stage | AI score |
|---|---|---|
| Applied AI/ML Lead Lead the deployment and scaling of advanced generative AI, agentic AI, and classical ML solutions within Cloud Foundational Services. This role involves designing and executing enterprise-wide AI/ML frameworks, owning product analytics and measurement strategy, building predictive models, and developing tools for prompt-based agent evaluation and optimization. The position requires strong Python, SQL, and GenAI/RAG fundamentals, with a focus on building production-ready AI systems and providing technical leadership. | AgentServe | 8 |
| Image Applied AI ML Director Executive Director to architect and operationalize the AI strategy for Image as a Service, focusing on improving engineering efficiency, standardizing solutions, and institutionalizing responsible AI practices. The role involves leading the development of an infrastructure digital twin and establishing a use case governance framework. |
| Agent |
| 7 |
| Executive Director, Applied AI/ML – Image as a Service Executive Director to architect and operationalize the AI strategy for Image as a Service, focusing on embedding AI to reduce toil, improve reliability, and drive adoption of AI within image engineering and SRE domains. The role involves leading the development of an infrastructure digital twin, establishing a use case governance framework, and standardizing AI tooling. This is an individual contributor role with significant indirect leadership. | Agent | 7 |