Product Manager, AI Foundations & Data Pipelines

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

Job summary

Google is hiring a Product Manager for Autonomous AI Foundations Data Engineering Infrastructure, based in San Jose, CA. You will guide products from conception to launch, bridging the technical and business worlds to unlock scalable data pipelines and AI capabilities.

You will own the end-to-end lifecycle for evolving data engineering technologies, partner with AI Foundations teams to scale pipelines, and collaborate with engineers to remove infrastructure bottlenecks to accelerate model

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 (0 to 1, etc.).
• 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 evolving data engineering technologies.
• Partner with stakeholders across Google to drive innovative solutions and growth for use cases.
• Collaborate with engineering teams to build frameworks that remove infrastructure bottlenecks.
• Enable researchers to deploy large-scale feature pipelines to accelerate product velocity.
• Partner with cross-functional PMs across AI Foundations to advance data product capabilities.

Skills

PM experience

End-to-end PM

Backend infrastructure

Data pipelines

AI integration

Education

Bachelor's degree

Master's degree preferred

Job description

Google is hiring a Product Manager for Autonomous AI Foundations Data Engineering Infrastructure, based in San Jose, CA. You will guide products from conception to launch, bridging the technical and business worlds to unlock scalable data pipelines and AI capabilities.

You will own the end-to-end lifecycle for evolving data engineering technologies, partner with AI Foundations teams to scale pipelines, and collaborate with engineers to remove infrastructure bottlenecks to accelerate model