Product Manager, CTM Intelligence

Minimum qualifications:

• Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.

• 8 years of experience in product management, including experience taking a technical product from 0 to 1 or managing a product through a full lifecycle.

• Experience building and shipping products powered by Machine Learning, Natural Language Processing (NLP), or LLMs.

• Experience defining product roadmaps and strategy for platform-level initiatives impacting multiple product surfaces (e.g., Gmail and Google Chat).

Preferred qualifications:

• Experience building platformized services or infrastructure, specifically defining common vocabularies, APIs, or taxonomies used by other product teams.

• Experience in building intent detection systems, task management ecosystems, or workflow automation tools.

• Experience in leading ambiguous V1 projects within a large organization, and the ability to converge disparate roadmaps into a unified direction.

• Ability to partner closely with Engineering and Research teams to evaluate model performance, understand artifact classification, and optimize for agentic user experiences.

• Excellent written and verbal communication skills, with the ability to influence senior stakeholders and cross-functional partners across the Workspace organization.

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.

The Communications and Time Management (CTM) Intelligence team sits at the heart of the "AI-First" Workspace evolution. We are responsible for building the intelligence layer that understands user intent, manages complex task life-cycles, and automates messaging workflows across Gmail, Chat, and Calendar.

Why Join Us? We are a newly formed team managing some of the most ambiguous and high-impact "Agentic AI" problems at Google. You will define how millions of users interact with AI to stay on top of their day, moving beyond simple organization to proactive assistance. If you are passionate about Large language Model (LLM) orchestration, intuitive UX for complex tasks, and redefining the future of work, we would love to have you build this with us.

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:

• Define and platformize universal intent detection across Gmail and Chat, establishing a common vocabulary for message and artifact annotation.

• Architect the foundational platform layer necessary to enable sophisticated follow-on actions and autonomous AI agents.

• Own end-to-end artifact understanding, leading the development of classifiers to extract high-signal information (e.g., meeting suggestions) and trigger contextual actions across surfaces.

• Partner with Engineering and Research to solve high-ambiguity problems in LLM orchestration, ensuring intent detection is both universal and actionable.

• Influence cross-functional roadmaps to ensure automation features, like auto-labeling based on trip or project context, are integrated seamlessly into the user experience, this includes driving the strategic direction and road map for Workspace Automation, converging it with AI Inbox initiatives to enable complex, multi-step user actions.