Field Solution Architect, AI Infrastructure, Google Cloud

TECHNICAL_SOLUTIONS
USA
April 13, 2026
FULL_TIME

Job Overview

  • Date Posted
    April 13, 2026
  • Location
    USA
  • Expiration date
    --

Job Description

2026-04-08T13:31:15.617Z

118709482589954758

The application window will be open until at least April 15, 2026. This opportunity will remain online based on business needs which may be before or after the specified date.

Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.
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: New York, NY, USA; Atlanta, GA, USA; Austin, TX, USA; Boulder, CO, USA; Chicago, IL, USA; Seattle, WA, USA; San Francisco, CA, USA; Sunnyvale, CA, USA.

Minimum qualifications:

  • Bachelor’s degree in Computer Science, Mathematics, a related technical field, or equivalent practical experience.
  • 7 years of experience with cloud infrastructure (e.g., hardware shapes, sizes, auto-scaling, auto-provisioning), and experience with infrastructure as a service, platform as a service, and software as a service.
  • Experience coding in Python, bash scripting, and using OSS frameworks (e.g., TensorFlow, PyTorch, Jax).
  • Experience with distributed training and optimizing performance versus costs (e.g., PyTorch FSDP/DeepSpeed, JAX/pjit, bfloat16 mixed-precision, or MLPerf benchmarking).
  • Experience with orchestrators (e.g., Slurm, Kubernetes).
  • Experience building and operationalizing machine learning models.

Preferred qualifications:

  • Experience training and fine tuning large models (i.e., image, language, segmentation, recommendation, genomics) with accelerators.
  • Experience with containerization, K8s, Kubernetes on cloud.
  • Experience with running MLPerf benchmarks.
  • Experience with performance profiling tools (i.e., Tensorflow profiler, PyTorch profiler, Tensorboard).
  • Experience in designing and architecting large-scale AI compute clusters.
  • Ability to debug distributed training/inferencing code running.

About the job

The Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. We help customers transform and evolve their business through the use of Google’s global network, web-scale data centers, and software infrastructure. As part of an innovative team in this rapidly growing business, you will help shape the future of businesses of all sizes and use technology to connect with customers, employees, and partners.

As a Field Solution Architect, your experience and thought leadership will support Google Cloud sales teams to incubate, pilot, and deploy Google Cloud’s industry leading AI/ML accelerators (TPU/GPU) at AI innovators, large enterprises, and early stage AI startups. You will help customers innovate faster with solutions using Google Cloud’s flexible and open infrastructure.

In this role, you will identify and assess AI opportunities that would benefit from AI optimized infrastructure. You will help customers leverage accelerators within their overall cloud strategy by helping run benchmarks for existing models, finding opportunities to use accelerators for new models, developing migration paths, and helping to analyze cost to performance. Along the way, you would work closely with internal Cloud AI teams to remove roadblocks and shape the future of our offerings.

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.

The US base salary range for this full-time position is $183,000-$265,000 + 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

  • Serve as a trusted advisor to top customers, helping them incorporate artificial intelligence (AI) accelerators into cloud strategies by designing training and inferencing platforms.
  • Demonstrate Google Cloud differentiation through Proofs of Concept, feature demonstrations, model performance optimization, profiling, and benchmarking.
  • Collaborate seamlessly with the Google Compute Engine AI Infrastructure Dedicated Engineering Team to co-develop code artifacts, best practice documentation, and scalable machine learning (ML) solutions.
  • Influence Google Cloud infrastructure strategy by advocating for enterprise requirements and building repeatable assets to enable internal teams and customers.
  • Travel to customer sites and industry events as needed to provide direct support and represent Google Cloud AI solutions.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google’s EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

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