Applied AI Coach

Salesforce Salesforce · Enterprise · Atlanta, California - Irvine, New York - New York, Colorado - Denver, California - San Francisco, GA

Salesforce is seeking an Applied AI Coach to join their Outcome Acceleration team. This role focuses on ensuring AI agents meet customer needs and deliver real business results, bridging the gap between AI development and value realization. Responsibilities include designing success plans, resolving performance issues, leading business reviews with outcome data, and tracking AI agent deployment and adoption.

What you'd actually do

  1. Design and execute success plans to measure whether AI agents are meeting their goals and matching the original business case
  2. Run four-week sprints to diagnose and resolve performance issues when AI results are lagging
  3. Lead business reviews with customer teams, demonstrating tangible value through outcome data rather than simple usage reports
  4. Track AI agent deployment and adoption weekly to ensure stability in production

Skills

Required

  • Degree in Computer Science, Information Systems, Engineering, Data Science, or a related field
  • 1–3 years of work or internship experience in technical roles such as data analytics, engineering, or technical support
  • Proven ability to work directly with customers to solve problems and communicate technical concepts clearly
  • Hands-on experience with prompt engineering, vibe-coding tools, or LLMs
  • Strong analytical skills with the ability to interpret outcome models and prove the value of AI
  • Clear understanding of how AI systems and large language models function in a business setting

Nice to have

  • Experience diagnosing unexpected AI model behavior or model drift over time
  • Ability to craft compelling data narratives that support executive decision-making
  • A GitHub portfolio showcasing AI experiments or projects

What the JD emphasized

  • AI agents
  • business case
  • outcome data
  • AI deployment
  • prompt engineering
  • LLMs
  • AI systems
  • large language models
  • AI model behavior
  • model drift

Other signals

  • customer success
  • AI deployment
  • business outcomes