Customer Value Architect & Journey Mapping Lead - Enterprise Sales Enablement

Meta Meta · Big Tech · Menlo Park, CA +2

This role focuses on understanding and improving the customer journey for enterprise AI products, identifying friction points, and leveraging AI tools to optimize workflows. It involves research, cross-functional collaboration, and ensuring responsible AI practices.

What you'd actually do

  1. Own qualitative and quantitative research and documentation as it pertains to the success journey for our covered accounts, beginning with Large Enterprise (Fortune 500)
  2. Understand our existing customers, their use cases, jobs to be done in a deployment, common pain points and how business messaging can address customer needs
  3. Work cross-functionally with teams such as Marketing, Global Business Solutions (Sales), Product Engineering, Partner Organization, Insights and analytics and Customer Success Managers in the field
  4. Document and demonstrate the current customer journey by developing visual journey maps which may include service blueprints, flowcharts, layouts, diagrams, charts, and models
  5. Analyze specific success motion performance and make recommendations of ways to improve the effectiveness of our customer success lifecycle

Skills

Required

  • consulting
  • process optimization
  • design thinking
  • customer research
  • communication
  • organization
  • business skills
  • analytical skills
  • technical skills
  • AI tools integration
  • responsible AI practices
  • AI skill development
  • prompt engineering
  • agent orchestration

Nice to have

  • web-analytics applications
  • digital whiteboarding solutions

What the JD emphasized

  • Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
  • Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
  • Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies