# Product Manager, AI at Glean Work

Glean Work is hiring a Product Manager, AI in Mountain View, United States. It pays $200k-$300k a year and Level rates it Works on AI ●●●○; you can [apply on Glean Work](https://jobsbylevel.com/go/01c728cc-b3ba-42dd-826a-5e19deb62295?utm_medium=ai-agent).

AI Level 3, AI centrality 69 out of 100. Mountain View, CA.

## Details

- Company: [Glean Work](https://jobsbylevel.com/companies/glean-work)
- AI level: AI Level 3 (score 69 out of 100)
- Location: Mountain View, CA
- Salary: $200k-$300k
- Posted: May 12, 2026
- Apply: https://jobsbylevel.com/go/01c728cc-b3ba-42dd-826a-5e19deb62295?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=product-manager-ai-at-glean-work-5f9db0

## Prepare for this job

The job page lists 4 likely interview questions for this offer, with a CV checklist: https://jobsbylevel.com/jobs/product-manager-ai-at-glean-work-5f9db0

## Description

About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more. You'll be deeply embedded where people get things done. You'll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company. About the Role: As a Product Manager on Glean's AI team, you will own the core systems that make our AI reliable, efficient, and measurably better over time. We're looking for deep skills and hands-on experience in one or both of the following areas: Agent harness : experience designing or shipping the execution layer around the model, including planning, tool calling, context management, sub-agents, skills, memory, and long-running tasks, and making the tradeoffs across intelligence, latency, and cost that determine how well agents perform. Evaluation : experience building the evalsets, benchmarks, judges, and labeled data that gate launches, compare models and harness changes, and drive continuous hill-climbing on quality. This is a highly technical, cross-functional IC role. You will work closely with AI engineering, data science, and platform marketing teams, and you will partner with leading model providers and help go-to-market teams turn quality improvements into customer proof points. You will: Set the product strategy and roadmap for your area, grounded in customer workflows, trace data, and eval results. Define what "good" looks like for agentic work, including correctness, helpfulness, formatting, efficiency, and reliability, and turn it into clear, measurable launch bars. Make evidence-based tradeoffs across models, prompts, tools, and harness changes, balancing quality against latency, cost, and capacity. Decide when to use frontier models versus post-training open-weight models for specific tasks, weighing quality, cost, latency, and control, and define the data and evals needed to make post-trained models competitive. Build and scale the operating model for evaluation, including datasets, LLM-as-judge systems, human labeling, and benchmarks. Turn failed runs, poor traces, and user feedback into prioritized product and quality improvements. Partner with model providers and

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