Field Application Engineer Manager, Cloud AI Infrastructure

Google LLC

Austin, Kirkland (TX, WA)

On-site

USD 236,000 - 329,000

Full time

3 days ago
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Benefits offered by this job

Health, dental, vision, life, and long
Disability insurance
401(k) with company match
Paid time off (vacation)
Sick time
Maternity/paternity leave
Holiday pay

Job summary

Google LLC is seeking an experienced Field Application Engineer Manager (Hardware) to lead a team supporting AI/ML infrastructure on Google Cloud hardware.

You will guide incident response, troubleshoot complex AI workloads, and collaborate with Product, Quality, and Engineering teams to improve products and deploy reliable AI infrastructure at scale.

Qualifications

  • Bachelor’s degree or equivalent practical experience.
  • 8 years of experience with Linux/Unix systems and debugging across hardware/software boundary.
  • 5 years of technical leadership experience.
  • 3 years of experience with technical infrastructure (deployment, maintenance, troubleshooting).
  • 3 years of debug/validation experience with CPU, GPU, or TPU.

Responsibilities

  • Lead a team for on-call activities and incident response.
  • Diagnose and resolve customer problems; develop investigation tools to improve productivity.
  • Collaborate with Product, Quality, and Engineering teams and engage with SRE teams.
  • Develop deep understanding of AI/ML workloads and hardware architectures; build faster diagnosis tools.
  • Advise internal stakeholders to resolve deployment and operational obstacles in AI infrastructure.

Skills

Linux/Unix
Debugging across hardware/software
Technical leadership
AI/ML workloads
Troubleshooting across stack

Education

Bachelor's degree in Computer Engineering/Electrical Engineering/CS or related field

Tools

Kubernetes
Slurm
TensorFlow
PyTorch
CPU/TPU debugging tools

Job description

corporate_fare Google place Austin, TX, USA ; Kirkland, WA, USA

X 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
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Austin, TX, USA; Kirkland, WA, USA.
  • Bachelor's degree in Computer Engineering, Electrical Engineering, Computer Science, or IT-related field, or equivalent practical experience.
  • 8 years of experience with Linux/Unix systems and experience in debugging issues across the hardware/software boundary on enterprise-grade server infrastructure.
  • 5 years of experience in technical leadership.
  • 3 years of experience with technical infrastructure (e.g., deployment, maintenance, and troubleshooting), and with quality and reliability of technical infrastructure.
  • 3 years of debug or validation experience with CPU, GPU, or TPU.
  • 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 with ML frameworks (e.g., TensorFlow, PyTorch), with the understanding of the AI/ML training and inference life-cycle.
  • Experience working with distributed systems, and familiarity with common solutions, design patterns, or best practices.
  • Familiarity with containerization and orchestration technologies like Kubernetes or Slurm in an on-premises or cloud environment.
  • Understanding of memory and high-speed IO technologies.
About the job

Google Cloud accelerates organizations’ ability to digitally transform their business with the best infrastructure, platform, industry solutions and expertise. We deliver enterprise-grade solutions that leverage Google’s technology – all on the cleanest cloud in the industry. 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.

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 Manager (Hardware Engineer), your team will serve as on-site, external-facing trusted advisors to customers. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $236000 - $329000 (USD) + 25% bonus target + equity + benefits

  • Lead a team that will participate in on-call activities, working with the primary responders to resolve system observations. Provide leadership, mentorship, and career development for team members.
  • Manage customer problems through effective diagnosis, resolution, or implementation of new investigation tools to increase productivity on AI/ML infrastructure.
  • Work closely with multiple Product, Quality, and Engineering teams to improve the product, and 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.

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