Principal Product Marketing Manager, Enterprise Context

Description

The company builds a Work AI platform that helps people work more effectively with AI. It started as enterprise search and now offers search, an AI assistant, and AI agents on one secure, open platform.

It provides more than 100 connectors to enterprise SaaS tools, lets customers choose their LLM, and offers APIs, so organizations can govern, scale, and tailor AI without being tied to one vendor or waiting through long implementation projects.

Its Enterprise Graph and Personal Knowledge Graph map links between people, content, and activity, so responses are personal and aware of context. Its AI agents draw on enterprise and public data, both structured and unstructured, past and real-time, to automate work across teams. The company points to faster onboarding, hours of productivity gained each week, and better-informed decisions.

Customers span more than 50 industries, and the company has over 1,000 employees in more than 25 countries. Its systems run daily inside tools such as Microsoft Teams, Zoom, ServiceNow, Zendesk, and GitHub.

The engineering team ships agentic features on an open, extensible stack, where enterprise trust depends on careful work.

This Principal Product Marketing Manager role owns go-to-market for the context product, the technology behind reliable enterprise AI. Enterprise AI comes down to combining AI with enterprise data, and you will help tell that story to the market. You will turn work on context, connectors, indexes, graphs, semantic layers, and ontologies into clear product narratives, sharp positioning, and practical materials for customers.

You will work across product, engineering, research, sales, and communications, track a fast-moving data and AI market, and form a clear view of where it is heading. The role is visible and hands-on, suited to a marketer who can work closely with technical teams and explain complex ideas precisely. You will help position the company as a technical leader in next-generation enterprise AI.

Responsibilities

• Build and run the go-to-market strategy for the context product, covering new connectors, search quality, the Enterprise Graph, structured data, memory, and the context that makes AI experiences good.
• Work with Product and Engineering to turn architecture, technical trade-offs, roadmap priorities, and customer value into positioning, messaging, launch plans, and customer narratives.
• Run launches from start to finish: audience and release planning, communications, technical documentation, field enablement, customer education, and adoption after release. Set up launch processes that can be repeated.
• Shape the company's view of the emerging context stack for AI. Produce technical content and customer stories that show how teams can measure, improve, and trust AI apps and agents.
• Speak as a technical voice for the context product. Give Sales, Solutions Engineering, Customer Success, and partners the proof points and architecture they need to drive adoption.

Requirements

• At least 8 years of product marketing experience in B2B SaaS or a related field.
• A BA or BS in business, marketing, liberal arts, or a related field.
• Significant experience with data platforms, AI systems, or a closely related technical area.
• Deep understanding of modern AI data systems, including RAG, indexing, knowledge graphs, semantic layers, ontologies, and enterprise data architecture.
• Close tracking of the AI industry and enough technical credibility to speak with product, engineering, research, developers, and technical buyers. You explain technical decisions and market shifts in terms of customer and business impact.
• Strong technical writing and storytelling. You turn architecture, evaluation results, and capabilities into narratives and collateral without oversimplifying.
• A record of launching complex technical products and communicating with audiences from developers to executives, while influencing Product, Engineering, Sales, Customer Success, Communications, and Brand.
• Rigor about accuracy and evidence, comfort with ambiguity, and the ability to balance strategy with hands-on execution.
• Preferred: a technical bachelor's degree or equivalent practical experience.
• Plus: an MBA.

Conditions

Hybrid: four days a week in the Mountain View or San Francisco office.

Standard base salary range: $224,000 - $258,000 per year. Final pay depends on location, level, job knowledge, skills, and experience. Some roles may also be eligible for variable compensation, equity, and benefits.

The company works to build a diverse, inclusive workplace and does not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race.

The interview includes a short AI-focused exercise or discussion on how you think about, design, and use AI in your work. You may mention any tools, platforms, or workflows you use now. Prior experience with the company is not needed.

Benefits

• Competitive compensation and a full benefits package with medical, vision, and dental coverage.
• Generous time off and a 401k plan you can contribute to for long-term savings.
• A home office improvement stipend when you join.
• An annual education stipend and an annual wellness stipend.
• Regular company events and healthy lunches provided daily.