Product Manager, AI Foundations & Data Pipelines

Google LLC; San Jose (CA); On-site; USD 163,000 - 236,000; Full time

Job summary

Google in San Jose is seeking a Product Manager for AI Foundations Data Engineering to guide end-to-end product development. You will bridge technical and business needs, break down complex problems, and drive data pipeline innovations with engineering teams across the company.

In this role you will own the lifecycle of data engineering tech, collaborate with researchers, and shape solutions that accelerate model speed-to-market while aligning with broader AI Foundations strategies.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 5 years of experience in product management or related technical role.
• 2 years of experience taking technical products from conception to launch.
• Experience managing backend infrastructure and distributed data pipelines.
• Experience integrating generative AI tools or LLM interfaces into workflows.

Responsibilities

• Own the end-to-end product lifecycle, strategy, and roadmaps for key evolving data engineering technologies.
• Partner with stakeholders across Google and Alphabet to drive innovative solutions and grow products for emerging use cases.
• Collaborate with engineering teams to build frameworks and solutions that eliminate infrastructure bottlenecks.
• Enable researchers to deploy petabyte-scale feature pipelines to accelerate product velocity.
• Partner with cross-functional product managers across AI Foundations to advance the agentic capabilities of data products.

Skills

Product management

Backend infra

Data pipelines

AI/LLM integration

Education

Bachelor's degree or equivalent

Master's degree (preferred)

Job description

Google in San Jose is seeking a Product Manager for AI Foundations Data Engineering to guide end-to-end product development. You will bridge technical and business needs, break down complex problems, and drive data pipeline innovations with engineering teams across the company.

In this role you will own the lifecycle of data engineering tech, collaborate with researchers, and shape solutions that accelerate model speed-to-market while aligning with broader AI Foundations strategies.