Product Manager, aiEDU

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.

• 5 years of experience in product management or a related technical role.

• 2 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 integrating generative AI tools or LLM interfaces into workflows.

Preferred qualifications:

• Master's degree in a technology or business related field.

• Experience architecting personalization engines, recommendation systems, or content management platforms at scale.

• Experience in educational product development, teaching, or learning design.

• 2 years of experience in software development or engineering.

• 2 years of experience working cross-functionally with engineering, UX/UI, and other stakeholders.

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.

aiEDU team accelerates innovation for Googlers through personalized AI learning. We drive AI fluency across three pillars: technical onboarding, in-flow learning agents integrated into daily tools, and out-of-flow learning for tailored skill-building. We leverage generative AI to seamlessly integrate education into daily workflows.You will own the multi-year product outlook, platform architecture, and execution for Google's centralized AI learning ecosystem spanning our flagship destination hub, generative course creation, personalization nucleus, and community products.

You will lead execution cross-functionally to turn fragmented resources into a single compounding learning flywheel, partnering with executive stakeholders to align enterprise-wide upskilling strategy. Above all, our team is comprised of builders who stay engaged with modern AI tools, coding agents, and sandbox environments to rapidly build prototypes, validate concepts, and ship scalable platforms.

The Core team builds the technical foundation behind Google’s flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Google’s products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $163000 - $236000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google. Responsibilities:

• Define and own the multi-quarter product outlook, strategy, and roadmap for the learning product portfolio to unify platforms into a cohesive ecosystem.

• Lead the product architecture for the core personalization and content engine to dynamically assemble and tailor learning experiences.

• Drive cross-organizational alignment and federated partnerships with senior leaders to balance a rigorous baseline with tailored tracks.

• Act as a proficient builder by utilizing AI-native developer and prototyping tools to take ambiguous strategic concepts to working prototypes and user validation.

• Partner with cross-functional teams to establish causal telemetry and longitudinal measurement frameworks that connect destination learning to real-world behavioral outcomes.