Technical Program Manager II, NPI Deployment Planning, Technical Infrastructure

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 2 years of experience in program or technical project management.
  
• Experience with New Product Introduction (NPI), Data Centers, and Deployment Planning.

Preferred qualifications:

• 2 years of experience managing cross-functional or cross-team projects.
• Experience with capacity planning (e.g., network, power, and cooling), including the use of planning and optimization tools.
• Experience managing data center constraints and knowledge of data center physical layouts, infrastructure, and standards (e.g., power, space, cooling, operations, and network).
• Experience with data center, networking and machine deployments, including understanding of deployment process and the ability to drive tools and automation for continuous process improvement.
• Knowledge of New Product Introduction (NPI) process and Product Life Cycle (PLC), as it relates to hardware products for machine learning and high-performance computing.

About the job

A problem isn’t truly solved until it’s solved for all. That’s why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Technical Program Manager at Google, you’ll use your technical expertise to lead complex, multi-disciplinary projects from start to finish. You’ll work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate clearly with cross-functional partners across the company. You're equally comfortable explaining your team's analyses and recommendations to executives as you are discussing the technical tradeoffs in product development with engineers.

The Fleet Infrastructure team is focused on optimizing the value, as a function of cost, resiliency, sustainability, and agility, from Alphabet’s server across all data center envelopes. The team's outlook is that every machine tech is optimally deployable across the fleet with touchless space, power, network, and cooling planning. The team works to accomplish this by influencing products, ecosystems, and infrastructure.

As a Technical Program Manager, you will be focused on aligning new products and technical infrastructure interface roadmaps to enable fast, predictable, and optimized deployment of machines for all product areas across Google’s Data Center and third-party fleet.

Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.

The US base salary range for this full-time position is $132,000-$189,000 + 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.

Responsibilities

• Support the delivery of projects while managing data center constraints (e.g., power, space, cooling, operations, and network) in data center deployments, and focus on NPI deployments for high-performance computing initiatives.
• Create and manage physical layouts and standards, including the deployment impact and feasibility of NPIs, and define and manage tooling requirements for planning and delivery.
• Influence the development of new products and server floor design decisions, focused particularly on upcoming transitions in the ML and accelerator space, and build plans to help transition between successive product generations.
• Drive the development of new tools and decision-making frameworks for optimizing fleet lifecycle.
• Define standards and policies to simplify deployability of new ML and accelerator products, spanning TPU, GPU, and other product families across multiple product areas.