Job Description

Minimum qualifications

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in product management or a related technical role.
• 3 years of experience taking technical products from conception to launch (e.g., ideation to execution, end-to-end, 0 to 1, etc.).
• Experience developing or launching products or technologies within artificial intelligence or machine learning (AI/ML).
• Experience building developer platforms, APIs/SDKs, agentic protocols (e.g., Model Context Protocol (MCP)), or cloud storage/file-system primitives.

Preferred qualifications

• Master's degree in a technology or business related field.
• 5 years of experience in a business function or role (e.g., strategic marketing, business operations, consulting).
• 4 years of experience in a role preparing and delivering technical presentations to executive leadership.
• Familiarity with LLM agent architectures, context/RAG retrieval, or enterprise security, identity, OAuth scoping, and data governance (Data Loss Prevention (DLP), Access Control Lists (ACLs)).
• Track record of shipping 0-to-1 platform capabilities that bridge technical infrastructure and intuitive end-user/admin controls across complex cross-functional organizations.

About the job

At Google, we put our users first. The world is always changing, so we need Product Managers who are continuously adapting and excited to work on products that affect millions of people every day.

In this role, you will work cross-functionally to guide products from conception to launch by connecting the technical and business worlds. You can break down complex problems into steps that drive product development.

One of the many reasons Google consistently brings innovative, world-changing products to market is because of the collaborative work we do in Product Management. Our team works closely with creative engineers, designers, marketers, etc. to help design and develop technologies that improve access to the world's information. We're responsible for guiding products throughout the execution cycle, focusing specifically on analyzing, positioning, packaging, promoting, and tailoring our solutions to our users.

Google Drive crossed a billion human users; our next billion users will be AI agents. We are on a mission to transition Drive from a static repository of files into an active execution partner and the context, storage, and governance bedrock of the agent era.

On the Next Billion Agents pillar, we treat first-party and third-party agents as first-class users while keeping humans safely in control. As work shifts from single documents to multi-file trees and parallel agentic workflows, our team builds the foundational rails that let humans and agents collaborate at machine speed: Drive’s model context protocol platform and semantic retrieval, multiplayer agent attribution and comment collaboration, least-privilege folder sandboxing, agent skills and project extensibility, and rich HTML/Markdown artifact experiences.

AI will change the future of work in profound ways, and our products— Gmail, Docs, Drive, Calendar, Sheets, Vids and Meet are at the forefront. From pre-computed summaries for email threads, summaries for meetings, and videos created from a document using lifelike AI avatars, our AI opportunity is huge. Our mission is to meaningfully connect people so they can create, build, and grow together and as part of the team you can build how productivity tools should work 5-10 years into the future. You will work with model builders (Google DeepMind), work with exceptional leaders, and have the ability to impact billions of users across the world.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $192000 - $278000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Drive Agent Performance and Interop primitives—including Drive’s Model Context Protocol (MCP) server, semantic passage retrieval, event subscriptions, unshared agent scratch storage, and native support for emergent primitives like Skills and Workspace Projects.
• Lead Agent Governance, Trust and Safety capabilities—including clear write-time agent attribution across drive and editors, least-privilege folder scoping (Label-Based OAuth/App Access Tags), actor-based DLP, human-in-the-loop (HITL) approvals, and multi-file agent undo/version control.
• Deliver First-Class Agent Artifacts and Multiplayer UX—enabling humans and agents to coordinate in comments and view, critique, and promote agent-generated Markdown, HTML, and multi-file outputs into shared workflows.
• Partner closely with Engineering, UX, Data Science, Security, and cross-Workspace partner teams (Gemini Enterprise, Documents/Editors, Cloud/Platform) to grow weekly active agents (WAAs) and governed agent file activity.