About the Role
Glean is seeking a talented AI Outcomes Manager to join our rapidly expanding team. The AI Outcomes Manager will play a crucial role in transforming how every department works, with the power of Glean. They will work closely with executives and end users, combining business acumen, product sense, and prompting skills to help them transform into an AI-native enterprise.
Responsibilities
- Partner with executive sponsors and end users to identify high‑impact use cases and turn them into measurable business outcomes on Glean.
- Lead strategic reviews and advise customers on their AI roadmap, ensuring they get the most value from Glean’s platform.
- Translate business needs into clear problem statements, success metrics, and practical AI solutions; collaborate with Product and R&D to shape priorities.
- Conduct discovery workshops, scope pilots, and guide rollouts, driving breadth and depth of adoption of the Glean platform.
- Design and build AI agents with and for customers, including rethinking and redesigning underlying business processes to maximize impact and usability.
- Proactively identify expansion opportunities and drive engagement across teams and functions.
Requirements
- 5+ years of professional experience in roles that blend business and technology (e.g., product, analytics, data, engineering, solutions), with a consultative, customer‑facing approach.
- Strong problem‑solving and communication skills; comfortable working with stakeholders from ICs to executives and tailoring messages to different audiences.
- Demonstrated ability to craft effective prompts and guide AI agents for real customer or business workflows; you’ve shipped outcomes, not just demos.
- Understanding of what current LLMs can and cannot do; able to set expectations and steer towards reliable, safe, cost‑effective solutions.
- Product sense and user empathy—you can spot high‑value applications of AI across diverse job functions and design clear, guided experiences.
- Hands‑on experience with modern AI platforms and tools (e.g., OpenAI, Claude, Mistral, Cohere or similar), with enough technical depth to work with engineers without needing to be on the critical path for writing production code.
Good to Have
- Prior experience in customer‑facing, consultative roles (solutions, support, product management) and 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.