Manager, Product Management - Genai Transformation (business Cards & Payments)

Capital One Capital One · Banking · McLean, VA +1

Product Manager to support the AI transformation for Capital One's Field Sales Organization. The role focuses on enabling GenAI-powered experiences by designing and building a horizontal foundation for shared, trusted context for AI applications, centralizing and standardizing data for downstream AI systems. The role also owns the end-to-end feedback loop strategy for continuous improvement of AI model performance and retraining.

What you'd actually do

  1. Design and build a horizontal foundation for shared, trusted context for AI applications.
  2. Centralize and standardize data so downstream AI systems can reliably access and leverage it to generate insights and recommendations.
  3. Own the end-to-end feedback loop strategy - ensuring AI outputs are systematically captured, evaluated, and fed back into the system to continuously improve model performance and retraining.
  4. Enable GenAI-powered experiences across the sales funnel.

Skills

Required

  • Product Management
  • Generative AI systems
  • measurement for GenAI in production
  • feedback loop mechanisms
  • AI performance improvement at scale

Nice to have

  • formal on-the-job experience with AI
  • incorporated AI into personal projects
  • explored AI-driven development environments
  • built automations using AI agents
  • translating business strategy and analysis into consumer facing digital products

What the JD emphasized

  • demonstrated interest and aptitude for Al
  • formal on-the-job experience with Al is a plus
  • proactively incorporated Al into their personal projects
  • explored Al-driven development environments
  • built automations using Al agents
  • used Al to learn, build, and solve problems beyond basic text generation
  • deep experience working with Generative AI systems
  • building measurement for GenAI in production
  • designing feedback loop mechanisms
  • operationalizing AI performance improvement at scale

Other signals

  • building a horizontal foundation for shared, trusted context for AI applications
  • centralize and standardize data so downstream AI systems can reliably access and leverage it
  • own the end-to-end feedback loop strategy
  • operationalizing AI performance improvement at scale