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 |
|---|---|---|
| Asset Management - AI Systems Engineer – Associate/VP The role focuses on building and optimizing enterprise LLM serving platforms, including GPU pooling, AI infrastructure, and MLOps for model deployment. It requires expertise in Python, Java, Kubernetes, and LLM inference engines, with a strong emphasis on performance optimization. | Serve | 8 |