Product Manager, Enterprise Intelligence

About Glean

Glean is the Work AI platform that helps everybody 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 is measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level.

We are a diverse, inclusive company that values every voice and strives to create a welcoming environment for all.

Glean is seeking a highly strategic and execution‑oriented Product Manager to define and build our emerging Enterprise Intelligence product area. This role sits at the intersection of AI, enterprise workflows, analytics, and product strategy. You will help shape how Glean turns its enterprise context layer into proactive, high‑value intelligence products that help leaders and teams understand what is changing, where value is being created or lost, and where to act.

• Help define and drive the product strategy and roadmap for Enterprise Intelligence, translating broad company vision into specific product bets, experiences, and execution plans informed by customer needs and market signals.
• Spend significant time with customers, prospects, and internal stakeholders to understand high‑value enterprise intelligence use cases, especially where organizations need proactive, contextual insights rather than reactive search or chat experiences.
• Build products that turn Glean’s enterprise context layer, graph, and connected system intelligence into actionable workflows, dashboards, recommendations, and proactive experiences for teams and leaders.
• Partner deeply with engineering, design, and data teams to turn ambiguous concepts into well‑scoped products, with clear user flows, interaction patterns, quality standards, and measurable outcomes.
• Drive customer‑focused prioritization and efficient execution, balancing long‑term platform opportunities with urgent user pain points, strategic customer asks, and company priorities.
• Collaborate closely with go‑to‑market, solutions, support, and forward‑deployed teams to learn from real customer problems and ensure our product strategy reflects enterprise realities, not just internal assumptions.
• Help establish the product foundations for a new category by identifying how Enterprise Intelligence should look across proactive insights, organizational visibility, process understanding, and cross‑functional decision support.
• Bring a high bar for product craft by specifying how opportunities should work in practice, including concrete workflows, UI behavior, and adoption paths.

• 5+ years of experience in product management, with a track record of owning and shipping meaningful product areas in B2B SaaS, enterprise software, AI products, analytics products, or workflow/intelligence platforms.
• Strong product sense for translating complex, ambiguous problems into clear product experiences, and comfortable moving between strategy and detailed execution.
• Deep interest in AI and enterprise software, excited by the opportunity to shape products that combine context, workflows, analytics, and proactive intelligence.
• Strong technical fluency and comfortable partnering with engineering and data teams on systems involving structured and unstructured data, knowledge graphs,…