The role
From JPMorgan Chase's own posting.
Join us as we build the next generation of AI and autonomous agents to solve critical operational challenges at the scale of the world’s largest bank. You will have the opportunity to shape product strategy and delivery, working with cutting-edge technologies and collaborating with leaders across Product and Technology. Your expertise will help us translate business needs into impactful solutions, leveraging LLMs, agentic orchestration, and ML platforms. This is your chance to make a measurable impact and advance your career in a dynamic, innovative environment.
As an AI Product Manager in the Corporate and Investment Banking operations team, you will lead the strategy and delivery of AI-driven products that automate and improve key operational workflows. You will partner with cross-functional teams to translate business requirements into actionable roadmaps and shipped capabilities. Your role will focus on driving measurable business outcomes, fostering collaboration, and ensuring alignment across stakeholders. You will help shape the future of AI at JPM, contributing to a culture of innovation and excellence.
Job Responsibilities:
Identify high-impact use cases where AI and agentic services improve key performance indicators.
Own product strategy, roadmap, and product requirements documents to enable platform capabilities.
Lead project teams of engineers, designers, analysts, and business leads through technical and non-technical decisions to launch.
Develop and execute comprehensive project plans, incorporating technical requirements, resource estimates, and timelines.
Communicate and drive alignment with senior stakeholders, securing buy-in and unblocking decisions.
Required Qualifications, Capabilities, and Skills:
Significant product management or related technical experience delivering AI products end-to-end.
Ability to ship AI-enabled products and lead complex programs in large, matrixed organizations.
Experience driving the full product lifecycle, writing product documents, and leading technology teams from idea to execution and launch.
Familiarity with AI model architectures, including Large Language Models, and methods such as prompting, context engineering, fine-tuning, retrieval augmented generation, model context protocols, and agentic frameworks.
Excellent stakeholder management, structured thinking, and ability to connect product work to business outcomes.
Preferred Qualifications, Capabilities, and Skills:
Experience designing robust evaluation sets and running quantitative and qualitative iterations to achieve reliable production quality.
Familiarity with cloud and data platforms, such as AWS, data management, and machine learning tooling.
Advanced degree in a relevant field.