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 1184 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 Quant Analyst - Artificial Intelligence & Machine Learning Focus JPMorgan Chase is seeking an AI Quant Analyst with a focus on AI/ML for their Asset Management division in Shanghai. The role involves researching and implementing quantitative investment models using ML/DL, applying LLMs/NLP to financial data for insights, and collaborating with teams to deploy models. The position requires a Master's or PhD in a quantitative field, 3+ years of experience in quantitative research within finance, and proven expertise in ML/DL/AI, particularly LLMs/NLP for financial data. Strong coding skills in Python and experience with statistical modeling are essential. The role also requires knowledge of financial markets and regulatory compliance. | Post-trainAgent | 8 |