About the role

What will you do at Google?

MINIMUM QUALIFICATIONS:

* Bachelor's degree or equivalent practical experience.

* 8 years of experience in product management or related technical role.

* 2 years of experience working with Infrastructure as a Service (IaaS) and

Kubernetes.

* 2 years of experience in infrastructure platforms, microservices, or agentic

architectures.

* Experience in the development or launch of products or technologies within

artificial intelligence or machine learning (AI/ML).

PREFERRED QUALIFICATIONS:

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

* 4 years of experience in a role preparing and delivering technical

presentations to executive leadership.

* 3 years of experience in software development or engineering.

* Experience with AI/ML in security.

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.
ACI Infrastructure delivers the secure, reliable, and unified compute
infrastructure powering Google Cloud’s scale. As the foundational glue between
hardware NPIs, orchestration, and workloads, we are accountable for the
non-negotiable bedrock of platform security and reliability.
The opportunity ahead puts us in the middle of the most impactful work for
Google Cloud.
Our mission is to deliver the world's most complete and powerful AI substrate
into an uneventful, predictable, and infinitely scalable utility for the Agentic
era. This high-stakes engineering represents a unique chance to decouple revenue
from hardware constraints.
The AI and Infrastructure team is redefining what’s possible. We empower Google
customers with breakthrough capabilities and insights by delivering AI and
Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our
customers include Googlers, Google Cloud customers, and billions of Google users
worldwide.
We're the driving force behind Google's groundbreaking innovations, empowering
the development of our cutting-edge AI models, delivering unparalleled computing
power to global services, and providing the essential platforms that enable
developers to build the future. From software to hardware our teams are shaping
the future of world-leading hyperscale computing, with key teams working on the
development of our TPUs, Vertex AI for Google Cloud, Google Global Networking,
Data Center operations, systems research, and much more.
Individual pay is determined by factors including job-related skills,
experience, and relevant education or training.
US: $192000 - $279000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google
[https://www.google.com/about/careers/applications/benefits/].
RESPONSIBILITIES:
* Evolve the GKE Node OS roadmap (COS, Ubuntu, Windows), aligning release
cadences with Kubernetes and optimizing for security and reduced downstream
toil.
* Drive the customization strategy, including GKE Image Builder, balancing
customer demands for flexibility (BYONI, non-mainstream OSs, custom kernels)
with platform supportability.
* Oversee predictable upgrade-in-place strategies to eliminate
customer-experienced downtime during capacity constraints.
* Guide the transition and technical enablement for new CPU NPIs across GKE
Standard and Autopilot, including Day 0 support.
* Partner with engineering to deliver runtime primitives for GPU/TPU workloads,
including containerd strategic alignment, Pod Snapshotting, and image
streaming.

Which skills does this role require?

Product ManagementInfrastructure as a ServiceKubernetesMicroservicesAgentic ArchitecturesTechnical PresentationsGKE Node OSGPU/TPU WorkloadsPlatform SecurityCloud InfrastructureMachine LearningIaaSGKETPUGPUVertex AICloud ComputingHyperscale ComputingContainerdPod SnapshottingImage StreamingNPINode.jsGCPProduct Strategy

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