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 reference: agent orchestration, llm observability, model serving, rag, fine tuning.
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 |
| Applied AI/ML Lead Lead the design, development, and production deployment of AI/ML solutions for image classification, text categorization, and data extraction from scanned documents using computer vision and NLP models. Architect and implement scalable ML training and inference pipelines on AWS SageMaker, integrating with microservices and establishing MLOps practices. Build and manage a team of ML engineers and applied scientists. | ServePost-train |
| 8 |
| SR Principal Software Engineer - LLM Engineering Senior Principal Software Engineer focused on LLM Engineering within JPMorgan Chase's Trust & Safety Fraud Prevention team. The role involves architecting, building, and optimizing model serving solutions, particularly for LLMs and GNNs, across cloud and on-premises environments. Key responsibilities include defining MLOps/LLMOps strategies, driving inference optimization for high throughput and low latency, creating reusable ML engineering frameworks, and ensuring observability, reliability, and cost efficiency in production AI workloads. | Serve | 8 |
| Principal Software Engineer Principal Software Engineer at JPMorgan Chase focused on designing, implementing, and scaling AI/ML infrastructure and platforms on AWS. The role involves collaborating with teams, developing and optimizing ML models, leveraging Databricks, and leading the productionalization of Gen AI use cases. Requires strong experience in AI/ML engineering, LLM Ops, model serving, and fine-tuning. | ServePost-train | 8 |
| Principal Software Engineer Principal AI/ML and Gen AI Engineer at JPMorgan Chase focused on scaling AI/ML infrastructure and platforms for model serving and fine-tuning, with expertise in LLM Ops and productionalizing Gen AI use cases on AWS and Databricks. | ServePost-train | 8 |
| Lead Software Engineer - Fullstack Java/AWS/AI/ML Lead Software Engineer role focused on full-stack development (Java/Python/JS) with a strong emphasis on integrating and deploying AI/ML models, including edge deployment. The role involves building, training, fine-tuning, and optimizing models, managing their lifecycle, and deploying them on AWS infrastructure. It also requires driving team adoption of AI-assisted engineering practices and ensuring responsible AI use within development workflows. | ServePost-train | 7 |
| E-Markets [Multiple Positions Available] This role focuses on managing and optimizing electronic credit trading algorithms, involving price delivery, risk management, and data analytics. It requires experience in developing event-oriented processing engines, performing predictive modeling with deep learning methods (RNNs, LSTMs), and data analysis using various tools like Java, Python, kdb, SQL, and Tableau. The goal is to improve trading operations, manage risks, and provide solutions for clients' trading strategies within a fintech environment. | Serve | 7 |
| Lead Software Engineer – Python / Java - AI -Markets Technology, Credit Pre-Trade Technology Lead Software Engineer role focused on building and supporting AI-native systems to enhance eTrading capabilities within JPMorgan Chase's Credit Pre-Trade Technology team. The role involves designing, developing, and troubleshooting critical technology solutions, with a strong emphasis on leveraging AI for trading platforms and modernizing existing systems. It requires hands-on experience with AI components, cloud services, and agile methodologies, and involves direct collaboration with business partners. | ServeAgent | 7 |
| Data Scientist [Multiple Positions Available] This role focuses on designing, developing, and deploying machine learning models for security platforms, specifically for enforcing least privilege access. It involves data processing, feature engineering, MLOps, production deployment, and ensuring compliance with security requirements within an AWS environment. | ServeData | 7 |
| WFP Senior Data Scientist Senior Data Scientist at JPMorgan Chase focused on building AI/ML solutions for workforce planning, including demand forecasting, capacity optimization, and scheduling. The role involves framing ambiguous problems, selecting appropriate modeling approaches, and productionizing solutions for real-time inference and decision-making within large-scale operations. | Serve | 7 |
| Lead Software Engineer - AI/ML Lead Software Engineer focused on building and scaling machine learning platforms and infrastructure at JPMorgan Chase. Responsibilities include designing, developing, and optimizing tools for the end-to-end ML lifecycle, integrating various ML capabilities, and ensuring platform reliability and security. Requires strong software engineering background, experience with ML platforms and MLOps, and Python proficiency. | Serve | 7 |
| Sr Lead Software Engineer - AI/ML Senior Lead Software Engineer focused on building, scaling, and maintaining robust machine learning platforms and infrastructure. The role involves designing and optimizing tools for the end-to-end ML lifecycle, including data engineering, feature management, model training, deployment, monitoring, and serving. Emphasis on secure, high-quality production code, MLOps practices, and collaboration with data scientists and ML engineers to accelerate ML development and operations within an enterprise environment. | ServeData | 7 |
| AI Platform Engineer, Python - Principal Software Engineer As a Principal Software Engineer at JPMorgan Chase, you will provide expertise and engineering excellence to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. You will execute creative software solutions, design, development, and technical troubleshooting for AI-enabled applications, create complex and scalable coding frameworks, and develop secure and high-quality production code. You will also advise cross-functional teams, serve as a subject matter expert, and contribute to the development of technical methods. The role requires formal training or certification on software engineering concepts, 7+ years of applied experience, DevOps experience, advanced Python skills, practical cloud-native experience, and experience in Computer Science or a related technical field. Experience with building AI platforms is highly preferred. | Serve | 7 |
| Applied AI ML Lead - ML Ops, CTC ML Ops Engineer role focused on deploying, monitoring, and managing machine learning models in production environments within JPMorgan Chase's Cybersecurity team. Responsibilities include building CI/CD pipelines, optimizing infrastructure, and ensuring reliable and efficient AI system performance. | Serve | 7 |
| Quantitative Trading & Research - Credit - Vice President Seeking a VP to join Credit Quantitative Trading team, leveraging AI/ML to enhance trading strategies and decision-making. The role involves exploring and integrating AI/ML methodologies, developing and deploying models end-to-end in production, and ensuring robustness and scalability. Requires experience in quantitative research, fixed income markets, and AI/ML timeseries models. | ServePost-train | 7 |
| Lead Software Engineer - AI/ML Deep Learning & GPU ML Serving Lead Software Engineer focused on AI/ML Deep Learning and GPU ML Serving within a Commercial and Investment Banking team. Responsibilities include designing, developing, and troubleshooting software solutions, writing production code, producing architecture artifacts, analyzing data, and optimizing deep learning models for inference. The role requires experience with ML systems, Python, ML frameworks, cloud technologies (Docker, Kubernetes), ML model serving frameworks, GPU workloads, low-latency systems, and NoSQL databases. Experience with GPU resource management and microservices architecture is also needed. Preferred qualifications include an advanced degree, proficiency in multiple programming languages, experience with graph neural networks, GPU programming, model monitoring, MLOps tools, and serving large-scale models. | Serve | 7 |
| Software Engineer III - AI/ML Deep Learning & GPU ML Serving Software Engineer III at JPMorgan Chase focused on AI/ML Deep Learning and GPU ML Serving. The role involves developing, testing, and troubleshooting software solutions, writing production code, producing architecture artifacts, analyzing data, and optimizing deep learning models for production inference. Key responsibilities include deploying and managing GPU workloads in Kubernetes, building scalable, low-latency systems, and partnering with product teams. Requires formal training/certification, 3+ years of applied experience, proficiency in Python and ML frameworks, experience with cloud technologies (Docker, Kubernetes, EKS), ML model serving frameworks, GPU workloads in Kubernetes, and NoSQL databases. Familiarity with modern microservices architecture and leading large-scale system design is also needed. Preferred qualifications include an MS/PhD, Java proficiency, experience with graph neural networks, GPU programming, model monitoring, MLOps tools, and serving large-scale models. | Serve | 7 |
| Principal Software Engineer - High Performance Computing Principal Software Engineer focused on High-Performance Computing (HPC) to optimize AI/ML model training and inference. The role involves creating scalable coding frameworks, developing production code, advising cross-functional teams, and publishing patterns for ML model optimization on various architectures. Requires deep experience in HPC, accelerators, deep learning (LLMs), and AI/ML frameworks, with a focus on performance and scalability for financial services. | ServeData | 7 |
| Lead Software Engineer - Python AWS GenAI Lead Software Engineer to build and maintain production-grade ML pipelines and infrastructure at enterprise scale for JPMorgan Chase's MLCOE. This role focuses on designing, developing, and deploying end-to-end ML systems, from data ingestion to serving outputs, with a strong emphasis on AWS services, CI/CD, and performance monitoring. | ServeData | 7 |
| Lead Software Engineer- (Python) Lead Software Engineer role focused on building and deploying production-grade machine learning pipelines and systems at enterprise scale within JPMorgan Chase's ML Center of Excellence. The role involves designing, developing, and maintaining software, engineering data pipelines, feeding data into ML models, and deploying complete systems into production environments with a focus on scalability and reliability. | ServeData | 7 |