Senior AI Product Manager - AI and Agentic Product Strategy

JPMorgan Chase JPMorgan Chase · Banking · LONDON, LONDON, United Kingdom · Commercial & Investment Bank

Product Manager role focused on defining strategy and delivery for AI-driven products and autonomous agents, leveraging LLMs and agentic orchestration within a large financial institution. Responsibilities include identifying use cases, owning product strategy and roadmaps, leading cross-functional teams, and communicating with senior stakeholders to launch AI-enabled products end-to-end.

What you'd actually do

  1. Identify high-impact use cases where AI and agentic services improve key performance indicators.
  2. Own product strategy, roadmap, and product requirements documents to enable platform capabilities.
  3. Lead project teams of engineers, designers, analysts, and business leads through technical and non-technical decisions to launch.
  4. Develop and execute comprehensive project plans, incorporating technical requirements, resource estimates, and timelines.
  5. Communicate and drive alignment with senior stakeholders, securing buy-in and unblocking decisions.

Skills

Required

  • 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.

Nice to have

  • 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.

What the JD emphasized

  • delivering AI products end-to-end
  • Ability to ship AI-enabled products
  • leading technology teams from idea to execution and launch

Other signals

  • AI and autonomous agents
  • LLMs, agentic orchestration, and ML platforms
  • AI-driven products that automate and improve key operational workflows
  • 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