Product Manager II, AI Inference, Google Kubernetes Engine Full-time

Minimum 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 with the domain area of Generative AI or Large Language Models.
• Experience with artificial intelligence, Generative AI/Generative AI workloads, AI training, AI inference, AI infrastructure, ML Operations, NVIDIA GPUs, or TPUs.

Preferred qualifications:

• Master’s degree in a technology or business related field.
• 3 years of experience in a business function or role (e.g., strategic marketing, business operations, consulting).
• 3 years of experience in a role preparing and delivering technical presentations to senior leadership.
• 2 years of experience in software development or engineering.
• 2 years of experience working cross-functionally with engineering, UX/UI, sales finance, and other stakeholders.
• Knowledge of Kubernetes, Containers, and Cloud Native ecosystem, with the ability to influence multiple stakeholders without direct authority.

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.

Google Kubernetes Engine (GKE) is a scalable and fully automated Kubernetes service available from any public cloud provider, enabling developers and businesses to run their containerized applications on Google Cloud. The GKE AI team is focused on making GKE the best place for customers to run their AI workloads. The GKE AI inference team is dedicated to ensuring GKE provides customers the best cost efficiency, scalability, and time-to-value for their AI inference workloads.

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 $142,000-$211,000 bonus equity benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. 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 .

Responsibilities

• Work with partner teams (e.g., engineers, program managers, UX) during product design and development to implement the requirements to turn PRDs into OKRs for one or more teams.
• Drive launches, maintenance, and retirement in collaboration with other cross-functional teams and stakeholders.
• Create solutions that differentiate GKE for serving AI inference workloads.
• Work with GKE customers who are critically important to GKE AI business growth and to diversify GKE’s AI customer base.
• Collaborate with partner organizations especially Cloud ML Compute Services (CMCS) to ensure the needs of GKE customers are incorporated into their roadmap and product plans, as well as to ensure Google Cloud ships a single coherent product experience that’s not fragmented by the organizational structure.