{"id":4301606,"url":"https://alion.io/job/google-customer-quality-engineer-cloud-ai-infrastructure-2","title":"Customer Quality Engineer, Cloud AI Infrastructure","company":{"id":82,"name":"Google","domain":"google.com","url":"https://alion.io/company/google","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":{"grade":"B","score":78,"open_postings":131,"ghost_share":0.038,"stale_share":0.763,"repost_share":0.038,"time_to_fill_p50_days":30,"computed_at":"2026-11-12T10:38:37Z"}},"role":"QA","role_family":"QA","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Austin, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"GCP","optional":false},{"name":"TPU","optional":false},{"name":"Kubernetes","optional":true},{"name":"SLURM","optional":true}],"status":"live","first_seen_at":"2026-11-13T22:06:52Z","employer_posted_date":"2026-11-14","last_verified_at":"2026-11-14T03:33:18Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"About the job\nOur AI Infrastructure Engineering Support team is dedicated to ensuring our customers get the most out of their Google Cloud hardware investment. As a Customer Quality Engineer (Hardware Engineer), you will be working alongside customers, understanding and improving hardware quality. You will be driving multiple complex technical challenges, understanding customer impacts, and driving internal and external teams to maximize quality. In this role, you will represent the customer, collaborating with engineering and product teams to drive continuous improvement in our products and services.\nGoogle 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.\nIndividual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $159000 - $230000 (USD) + 15% bonus target + equity + benefits\nLearn more about benefits at Google.\nResponsibilities\nTrack and manage customer hardware observations, helping guide priorities and resolution\nJoin with internal engineering teams to understand diagnosis and gauge impact resolution or implementation of new investigation tools to increase productivity on AI/ML infrastructure.\nWork closely with multiple Product, Quality, and Engineering teams to improve the product. Interact with our Site Reliability Engineering (SRE) teams to drive high-quality attainment. \nUnderstand the reliability and quality implications of hardware and software modifications and help teams understand how modifications could impact deployed hardware\nWork directly with customers to understand hardware quality, track future quality improvements, and manage future changes that could improve quality on deployed hardware.\nQualifications\nMinimum qualifications:\nBachelor's degree in Computer Science, Management Information Systems, or other technical field, or equivalent practical experience.\n4 years of manufacturing or validation experience with CPU, dGPU, or TPU.\n3 years of experience with quality and reliability of technical infrastructure.\nExperience with semiconductor and production manufacturing flows, and implementing test screens, ATE and DFT tests, and transistor parametrics. \nExperience troubleshooting and advocating for customer needs.\nExperience with System Architecture (CPU, TPU, I/O interfaces, or memory).\nPreferred qualifications:\nExperience working with distributed systems, and familiarity with common solutions, design patterns, or best practices.\nExperience working directly with AI/ML computing hardware, including GPUs or other accelerators.\nFamiliarity with containerization and orchestration technologies like Kubernetes or Slurm in an on-prem or cloud environment.\nExperience with systems automation, and systems design and debug.\nExperience working with vendors or customers.\nAdvanced understanding of transistor fabrication and ASIC assembly 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