Senior Director, Product Management, AI, Infrastructure
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- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Minimum qualifications:
- Bachelor's degree in Mathematics, Computer Science, or equivalent practical experience.
- 15 years of product management experience in enterprise hardware systems (compute, networking, storage) launching infrastructure and platform products.
- Experience as a builder of infrastructure products.
- Experience with AI Agents, inference models and AI infrastructure technologies (GPU Virtualization, Containerization) and their application in AI research.
Preferred qualifications:
- 8 years of experience as a leader of leaders.
- Experience partnering with hardware OEM vendors (e.g., Dell, NVidia).
- Understanding of genAI technology stack.
- Strong understanding of infrastructure technologies and trends, including public and private cloud, GPU, virtualization, containerization.
- Ability to collect/analyze market and customer data, and interpret and present complex information to drive strategic decision making to drive product strategy and decisions.
- Excellent organization, prioritization, and written/verbal communication skills.
About the job
Google Distributed Cloud (GDC) is a cloud-centric platform that enables enterprises to run modern apps anywhere consistently at scale. We offer a wide spectrum of solutions from managed software on your own hardware, fully managed hardware and AI-led software services, to completely air-gapped sovereign offerings.
As the Senior Director of Product Management for AI Infrastructure for GDC, you will define the long-term vision, strategy, and roadmap for a comprehensive AI-centric platform. This includes AI Agent frameworks, models 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.
Over time, we believe this team will define new products and services as part of the GDC portfolio that enable us to build large businesses by helping governments use AI for citizen services, manufacturers save time and money by using video for visual inspections on factory floors, and retailers to remove in-store hardware and create dynamic, modern applications.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.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $336000 - $467000 (USD) + 40% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Help to define the strategy for the GDC AI Platform, focusing on the deployment of autonomous AI Agents and optimized inference stacks across hardware profiles.
- 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 (e.g., NVIDIA, Dell) to co-design systems that are purpose-built for AI-first applications.
- Lead and retian a high-performing team of product managers, fostering a culture of 10x thinking.
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