The Chief Data & Analytics Office (CDAO) at JPMorgan Chase is responsible for accelerating the firm’s data and analytics journey. This includes ensuring the quality, integrity, and security of the company's data, as well as leveraging this data to generate insights and drive decision-making. The CDAO is also responsible for developing and implementing solutions that support the firm’s commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly

As an AI Product Manager Vice President within the Large Language Models (LLMs) team, you will have the unique opportunity to be a critical player in our firm-wide efforts to drive the adoption of LLMs across the firm. You will drive the product strategy, progression through the product development lifecycle, and partnership with technology partners necessary to deliver best-in-class products for the firm.  

Job Responsibilities 

Define a strategic vision and roadmap for the product that enables capabilities, governance, and operational metrics for LLMs that could include topics such as Supervised Fine-Tuning (SFT), and Reinforcement learning with human feedback (RLHF), RAG, Search, and Agents. Become the evangelist for the product vision across the firm and engage stakeholders across the Firm and demonstrate clarity, experience, and criticality of the product. Work with stakeholders across the various businesses (Investment Bank, Consumer Bank, etc.) and functional groups (Legal, Technology, Controls) to collect business requirements, create PRDs and ship high quality products that solve business needs/requirements.

Required qualifications, capabilities and skills 

6+ years of experience in product management with proven ability to lead and develop high performing product teams  Excellent leadership and collaboration skills, with the ability to positively influence and inspire technology teams and stakeholders  Strong track record of owning and developing a product domain strategy and roadmap. Able to balance short-term goals and long-term vision in highly complex environments Expertise on the AI lifecycle, spanning from data discovery, data processing, model development, model deployment, and model monitoring  Expertise in Cloud computing and architecture  Hands-on experience building or using LLM solutions. Experience in any of Supervised Fine-Tuning (SFT), and Reinforcement learning with human feedback (RLHF), RAG, Search, and Agents. Familiarity with LLM frameworks such as LangChain, OpenLLM, and Llama Index Knowledge of operationalizing LLMs responsibly through MLOps pipeline 

Preferred qualifications, capabilities, and skills 

Experience in Financial Services or other highly regulated industries