AI Outcomes Manager, West

Glean Glean · Enterprise · Mountain View, CA · Remote · Customer Outcomes

This role focuses on partnering with executives and end-users to identify and implement high-impact AI use cases using Glean's Work AI platform. The manager will translate business needs into AI solutions, design and build AI agents with customers, and drive adoption of the platform to achieve measurable business outcomes. The role requires a blend of business acumen, product sense, and prompting skills, with hands-on experience with modern AI platforms.

What you'd actually do

  1. Partner with executive sponsors and end users to identify high‑impact use cases and turn them into measurable business outcomes on Glean.
  2. Lead strategic reviews and advise customers on their AI roadmap, ensuring they get the most value from Glean’s platform.
  3. Translate business needs into clear problem statements, success metrics, and practical AI solutions; collaborate with Product and R&D to shape priorities.
  4. Conduct discovery workshops, scope pilots, and guide rollouts, driving breadth and depth of adoption of the Glean platform.
  5. Design and build AI agents with and for customers, including rethinking and redesigning underlying business processes to maximize impact and usability.

Skills

Required

  • 5+ years of professional experience in roles that blend business and technology
  • consultative, customer‑facing approach
  • Strong problem‑solving and communication skills
  • craft effective prompts and guide AI agents for real customer or business workflows
  • Understanding of what current LLMs can and cannot do
  • Product sense and user empathy
  • Hands‑on experience with modern AI platforms and tools (e.g., OpenAI, Claude, Mistral, Cohere or similar)

Nice to have

  • Prior experience in customer-facing, consultative roles (solutions, support, product management)
  • comfort presenting to senior leaders
  • Exposure to evaluating AI outcomes (e.g., defining success criteria, using sample tasks, reviewing results) and iterating for quality, latency, and cost.
  • Ability to analyze usage signals and customer feedback to inform roadmap and drive adoption.

What the JD emphasized

  • shipped outcomes, not just demos
  • hands-on experience with modern AI platforms and tools
  • enough technical depth to work with engineers without needing to be on the critical path for writing production code

Other signals

  • AI agents
  • Work AI platform
  • customer-facing AI solutions
  • measurable business outcomes