Field Application Engineer, Cloud AI Infrastructure

Google LLC; Kirkland (WA); On-site; USD 132,000 - 189,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Life insurance

Disability insurance

401(k) with company match

PTO 20 days per year

Sick time 40 hours/year

Maternity leave

Job summary

Google Kirkland, WA is seeking a Field Application Engineer to serve as a trusted advisor on on-site hardware analysis, debugging, and issue resolution for Google Cloud AI infrastructure. You will conduct in-depth investigations into complex technical problems, troubleshoot across the platform, and deliver expert solutions that enable customers to innovate confidently.

You will collaborate with Product, Quality, and Engineering teams, interact with Site Reliability Engineers, and help drive

Qualifications

• Bachelor's degree in Computer Science, MIS, or related field, or equivalent practical experience.
• 2 years of debug or validation with CPU, dGPU, or TPU.
• 2 years of experience with technical infrastructure deployment, maintenance, and troubleshooting.
• 2 years of hardware debug (silicon, platform IO, memory analysis).
• Experience with Linux/Unix and debugging across hardware/software boundary.
• Experience triaging issues across the stack (hardware faults, low-level software, networking, virtualization, kernel drivers, firmware, or performance).

Responsibilities

• Participate in on-call activities and manage server and data center CPU- and TPU-based activities, working with primary responders to resolve customer system observations.
• Manage customers' problems through effective diagnosis, resolution, or implementation of new investigation tools to increase productivity on AI/ML infrastructure.
• Work closely with Product, Quality, and Engineering teams to improve the product. Interact with our Site Reliability Engineering (SRE) teams to drive high-quality attainment.
• 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.

Skills

Field Applications Engineering

Hardware debugging

Linux/Unix proficiency

Cross-functional collaboration

Education

Bachelor's degree in CS/MIS or related

Tools

Linux debugging tools

System validation

CPU/GPU/TPU hardware

Job description

Share Field Application Engineer, Cloud AI Infrastructure

Google Kirkland, WA, USA

In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:

• Health, dental, vision, life, disability insurance
• Retirement Benefits: 401(k) with company match
• Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
• Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
• Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
• Baby Bonding Leave: 18 weeks
• Holidays: 13 paid days per year

• Bachelor's degree in Computer Science, Management Information Systems, a related technical field, or equivalent practical experience.
• 2 years of debug or validation experience with CPU, dGPU, or TPU.
• 2 years of experience with technical infrastructure (deployment or maintenance, and troubleshooting), and with quality and reliability of technical infrastructure.
• 2 years of experience with hardware debug (e.g., silicon, platform, IO interface, or memory analysis).
• Experience with Linux/Unix systems and debugging issues across hardware/software boundary on enterprise-grade server infrastructure.
• Experience troubleshooting and triaging technical issues across the stack (e.g., hardware faults, low-level software, networking, virtualization, kernel drivers, firmware, or performance).

Preferred qualifications:

• Experience working directly with AI/ML computing hardware, including GPUs or other accelerators.
• Experience with systems automation, and with systems design and debug.
• Experience working with vendors or customers.
• Experience working with distributed systems, and familiarity with common solutions, design patterns, or best practices.
• Experience with ML frameworks (e.g., TensorFlow, PyTorch), and understanding of the AI/ML training and inference lifecycle.
• Advanced understanding of memory and high-speed IO technologies.

About the job

Our AI Infrastructure Engineering Support team is dedicated to ensuring our customers get the most out of their Google Cloud hardware investment. As a Field Application Engineer (Hardware Engineer), you will be an on-site, external-facing trusted advisor to customers, driving hardware analysis, debug, and issue resolution. You will do in-depth research into complex technical issues, troubleshoot critical issues across the platform, and provide expert solutions that help customers innovate with confidence. In this role, you will represent the customer, collaborating with engineering and product teams to drive continuous improvement in our products and services.

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.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $132000 - $189000 (USD) + 15% bonus target + equity + benefits

• Participate in on-call activities and manage server and data center CPU- and TPU-based activities, working with primary responders to resolve customer system observations.
• Manage customers' problems through effective diagnosis, resolution, or implementation of new investigation tools to increase productivity on AI/ML infrastructure.
• Work closely with Product, Quality, and Engineering teams to improve the product. Interact with our Site Reliability Engineering (SRE) teams to drive high-quality attainment.
• 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.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.