Google Director, Product Management, GDC, AI-Led Services

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Job Details

Posted date: Feb 26, 2026

Location: Seattle, WA

Level: Executive

Estimated salary: $327,500
Range: $272,000 - $383,000


Description

Define the strategy for the GDC AI platform, focusing on the deployment of autonomous AI agents and optimized inference stacks across diverse hardware profiles. Oversee the GDC AI infrastructure portfolio, ensuring it provides the specialized accelerator performance required for large-scale AI workloads. Drive the development of tools and services that enable customers to build, deploy, and manage AI agents capable of automating complex tasks in edge and sovereign settings. Collaborate with engineering to minimize latency and maximize throughput for edge inferencing, supporting use cases like real-time computer vision and local LLM execution.

Partner with hardware OEMs to co-design systems that are purpose-built for AI-first applications.

As the Director of Product Management for Google Distributed Cloud (GDC), you will define the long-term vision, strategy, and roadmap for a comprehensive AI-centric platform. This includes not only the AI infrastructure (e.g., compute, storage, networking) foundations but also the AI agent frameworks and inference engines that allow enterprises to run modern applications anywhere consistently and at scale.

GDC empowers customers—from government agencies to global retailers—to run mission-critical, AI-led services in their own data centers or at the edge. You will lead the transition of GDC from a managed infrastructure provider to a robust on-prem AI platform that supports the entire lifecycle of autonomous agents and high-performance inferencing in air-gapped and connected environments.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

The US base salary range for this full-time position is $272,000-$383,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.



Qualifications

Minimum qualifications: 15 years of experience in product management, with experience launching infrastructure or platform products. Experience building distributed systems and GPU-accelerated platforms. Experience with infrastructure technologies (e.g., GPU, virtualization, containerization) and their application in AI research. Experience analyzing market data to drive strategy for emerging technologies like AI agents and edge inference.

Preferred qualifications: 8 years of experience as a second line people manager. Experience with the genAI technology stack, including LLM orchestration, inferencing, vector databases, and agentic workflows. Experience managing hardware OEM vendor relationships to deliver integrated software/hardware solutions. A passion for balancing bold AI innovation with responsible, secure deployment practices.

Extended Qualifications

15 years of experience in product management, with experience launching infrastructure or platform products. Experience building distributed systems and GPU-accelerated platforms. Experience with infrastructure technologies (e.g., GPU, virtualization, containerization) and their application in AI research. Experience analyzing market data to drive strategy for emerging technologies like AI agents and edge inference.

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