Customer Solutions Engineer, Compute, Google Cloud

About the job

The Google Cloud team helps companies, schools, and government seamlessly make the switch to Google products and supports them along the way. You listen to the customer and swiftly problem-solve technical issues to show how our products can make businesses more productive, collaborative, and innovative. You work closely with a cross-functional team of web developers and systems administrators, not to mention a variety of both regional and international customers. Your relationships with customers are crucial in helping Google grow its Cloud business and helping companies around the world innovate.

As a Technical Solutions Engineer, you will be a trusted advisor to a diverse range of customers. You'll look into complex technical challenges, troubleshoot critical issues across the Google Cloud platform, and provide solutions that help customers innovate with confidence. In this role, you will act as the voice of the customer, collaborating with engineering and product teams to drive improvement in our products and services.

You will be a part of a global team that provides 24x7 support to ensure customers can seamlessly deploy their AI and ML workloads on AI Infrastructure products. When customers encounter deep technical issues, your job is to ensure we have the expertise, tools, and processes to resolve the issue. You will troubleshoot technical problems with a mix of hardware and software debugging, networking, Linux system administration, coding/scripting, and updating documentation. You will help our customer’s success in the AI/ML space by making improvements to the product, internal tools, processes, and documentation. You'll help drive business growth by recognizing and advocating for our customers’ challenges related to AI deployments.

Responsibilities

• Manage customer’s problems through effective diagnosis, resolution, or implementation of new investigation tools to increase productivity for customer issues on AI/ML infrastructure.
• Develop an in-depth understanding of AI/ML workloads and underlying hardware architectures by troubleshooting, reproducing, determining the root cause for customer reported issues, and building tools for faster diagnosis.
• Act as a consultant and subject matter expert for internal stakeholders in Engineering, Sales, and customer organizations to resolve complex deployment and operational obstacles in AI infrastructure environments.
• Work closely with multiple Product and Engineering teams to find ways to improve the product, and interact with our Site Reliability Engineering (SRE) teams to drive high-quality production. 
• Be available for non-standard work hours or shifts which may include weekends as needed.