Description Our goal is to build the next generation of AI: autonomous agents that can reason, plan, act, and learn to solve critical problems for an industry-leading financial institution. We are looking for team members who will help define the future of banking through Agentic AI. The Applied Artificial Intelligence and Machine Learning team in Commercial and Investment Banking is transforming operations by leveraging the latest advancements in agentic AI and frontier models. As an Applied AI ML Senior Associate in this Applied AI Research team you will be a builder and scientific contributor who will help bridge the gap between leading-edge theory and enterprise-grade, large-scale, deployable systems. Job Responsibilities Contribute to the development of GenAI and Agentic solutions to automate complex operational processes Assist JPMC Lines of Business and teams in solving priority use cases within the domain Deliver agents that can collaborate to solve large, complex problems, orchestrate end-to-end workflows, and scale across JPMC Assist in designing and building services and libraries that AI teams want to use Participate in a culture of excellence, innovation, and continuous learning within the AI engineering team Contribute towards the scalability, reliability, and security of AI/ML solutions in a production environment, with a focus on long-term sustainability Collaborate with stakeholders and technical partners across Lines of Business and firmwide to scale solutions and maximize impact Required Qualifications, Capabilities, and Skills Research experience or experience working in a commercial AI research environment Strong understanding of AI fundamentals and practical experience with data analysis and experimental design Experience deploying AI/ML applications in a production environment Familiarity with distributed computing patterns for training, serving, and persistence of state Experience integrating user feedback to support agentic refinement and self-improving AI applications Experience working as part of a high-performing AI team Preferred Qualifications, Capabilities, and Skills: Experience deploying models on AWS platforms such as SageMaker or Bedrock will be strongly considered, but not required PhD level education