Product Manager, Stripe Infrastructure

Stripe Stripe · Fintech · United States · 8915 Core Tech Product Management

Product Manager for Stripe Infrastructure, focusing on internal AI agents for productivity and customer experience. The role involves defining and launching AI/ML-powered products, understanding LLMs, and working with engineering teams on AI solutions.

What you'd actually do

  1. Partner with the engineering teams, including Core Infra, Developer Infra, Data Platform, and Service Platform, to ship functionality that delights users, has the right balance of impact vs engineering cost, and makes a measurable impact on the business
  2. Establish system and design principles for how we build, buy, and operate Seller Systems — ensuring we select the right long-term solutions, not short-term patches.
  3. Guide architecture and investment decisions, weighing trade-offs between build vs. buy, modernization vs. extension, and platform vs. point solution to maintain a cohesive, sustainable ecosystem.
  4. Interact with external users and propose critical infrastructure abstractions that best serve them
  5. Work on internal AI agents for specific functions such as Recruiting, Legal etc. to aid productivity and great customer experience

Skills

Required

  • Product Management
  • launching and scaling complex products
  • managing diverse stakeholders
  • mapping, analyzing, and refining Customer User Journeys (CUJs)
  • AI solution deployment
  • data-driven approach to prioritization
  • defining key performance indicators (KPIs)
  • creating product impact dashboards
  • synthesizing data into actionable product requirements
  • leveraging qualitative and quantitative insights
  • Excellent written and verbal communication skills
  • articulate complex technical concepts
  • developing and launching AI/ML-powered products or features
  • Robust functional and technical understanding of Large Language Models (LLMs)
  • common AI-based workflows (e.g., retrieval-augmented generation, fine-tuning, prompt engineering)
  • working directly with LLMs or launching conversational AI agents into production
  • Technical background (e.g., Computer Science degree or equivalent practical experience)

Nice to have

  • Experience working with cross-geo/timezone environments
  • solving high-impact, cross-system challenges
  • aligning senior stakeholders

What the JD emphasized

  • Hands-on experience developing and launching AI/ML-powered products or features for internal or external customers.
  • Prior experience working directly with LLMs or launching conversational AI agents into production.

Other signals

  • AI agents for specific functions
  • AI solution deployment
  • LLMs
  • conversational AI agents into production