Minimum qualifications:

• Master's degree in Computer Science, Compute Architecture, or equivalent practical experience.
• 15 years of experience in software development, design, and architecture, data structures, logarithms, and testing.
• 8 years of experience with QA engineering delivery.
• Experience building and developing large-scale infrastructure, distributed systems, or networks, or experience with compute technologies, storage, or hardware architecture.

Preferred qualifications:

• PhD degree.
• Experience building software and large-scale distributed systems.
• Experience delivering within time-sensitive timelines.
• Understanding of private and public cloud design considerations and limitations in the areas of virtualization, global infrastructure, distributed systems, load balancing, networking, large-scale data storage, and security.
• Ability to work with globally distributed, cross-functional teams, partnering with groups (e.g., Supply Chain Operations, Sales, Engineering, Product Management, Product Marketing, UX and UI), brokering trade offs with stakeholders and understand their needs.

About the job

As Vice President, you will be responsible for driving the successful growth of global software engineering teams responsible for the development, testing and deployment of new products, programs, and hardware, all of which are used to support Google’s Platform Infrastructure. You will be responsible for providing a roadmap for product delivery and execution, driving strategy around our Cloud products that successfully deliver innovative solutions for our customers.

In this role, you will utilize a combination of direct development experience, management experience, and experience delivering complex projects and products. You will understand existing performance, quality and automation test frameworks, and have the ability to enhance and implement the same. You will manage a team of talented software developers and testers, oversee testing strategies, and ensure the highest standards of compliance, performance, and functionality. You'll collaborate closely with cross-functional teams to deliver innovative solutions, enhance testing processes, and ensure seamless transactions for customers worldwide.

The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.

We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.

The US base salary for this full-time position is $550,000 + bonus + equity + benefits. Individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.

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

• Develop a strategic outlook for the Google Data Center Infrastructure organization to constantly innovate and implement novel solutions for next-generation cloud software and services.
• Lead a large Engineering organization in all areas of compute infrastructure, deployment and testing, including enhancements to TI/Cloud/Storage/GPU/TPU based servers, ML Training, ML Inference, and YouTube transcoding.
• Drive the software quality metrics, focusing on continuous improvement. Design, build, and deploy the software infrastructure that powers all of Google and Cloud services.
• Manage robust and scalable systems in order to get ahead of the exponential market demand.
• Manage the health of production fleet and partner with internal supply chain business teams and external supply chain partners (e.g., suppliers, CMs, and 3PLs) in architecting and leading the the planning process for PIE.