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Location
In office (Sunnyvale)
Seniority
Architect · 10+ years exp

Confirmed on the employer's own hiring board on Nov 5, 2026. First seen by Alion on Nov 2, 2026. Google scores B on the Alion truth index.

Overview
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Google is an American technology company founded in 1998 by Larry Page and Sergey Brin and now the principal subsidiary of Alphabet, headquartered in Mountain View, California. It operates the world's dominant search engine and the advertising system built around it, along with YouTube, Android, Chrome, Gmail, Maps, Workspace and Google Cloud, reaching billions of users across nearly every internet-connected market. The company designs its own silicon in the Tensor Processing Unit line, develops the Gemini foundation models through Google DeepMind, and derives most of its revenue from advertising while cloud has become its fastest growing segment.

About the job

The Modular Manufacturing & Integration organization is leading an industry-defining transformation in how Google delivers technical infrastructure for the AI era. Transitioning away from conventional, on-site, purpose-built construction, our mission is to industrialize data center delivery through mass-assembled, standardized modules and off-site manufacturing.

By pushing labor-intensive assembly, systems integration, and quality testing upstream into controlled factory environments, we enable "square wave" capacity delivery-turning on gigawatt-scale AI compute, liquid cooling, power distribution, and network fabric with unprecedented velocity. Operating across AI Systems & Infrastructure (AI2), Google Data Centers (GDC), Systems & Manufacturing (ISM), and Google Global Infrastructure (GGI), our team defines the modular technical product and serves as the accountable business owner for industrializing and landing modular capacity globally.

As the Principal TPM of Manufacturing & Industrial Engineering, you will be the chief industrial architect responsible for translating Google’s modular infrastructure strategy into an executable, manufacturing reality. In this principal technical leadership role-with the charter to incubate the discipline and potentially scale a dedicated team over time-you will bridge the gap between design engineering, external contract manufacturing, and on-site field execution.

Your remit spans the entire physical and technical stack: structural modules, medium-to-low voltage power skids, liquid cooling distribution, and dense AI compute hardware. You will evaluate current field deployment and operations bottlenecks and establish scalable manufacturing processes with global contract manufacturers and fabricators. Your core mandate is simple yet radical: dramatically compress the timeline from factory gate to live AI compute, reduce complexity of assembly in manufacturing and in the field, and increase first pass yield/quality of the entire data center system.

The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.

We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.

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

US: $281000 - $391000 (USD) + 30% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

  • Formulate and drive the multi-year manufacturing and assembly roadmap for Google’s modular data center platforms, aligning complex system architectures with industrial factory capabilities.
  • Deconstruct monolithic data center systems into standardized, manufactured building blocks. Architect module boundaries across structural, cooling, power, and IT server clusters to maximize factory pre-assembly and minimize field connections.
  • Advocate for DFM/A, Design for Test (DFT), and modular interface standards upstream across Hardware Engineering, Data Center Engineering, and Infrastructure design teams, ensuring products are engineered from inception for rapid off-site assembly.
  • Dive into existing on-site data center construction, white-space fit-out, and compute commissioning processes. Identify labor-intensive operations and re-engineer them into off-site, factory-integrated steps.

Qualifications

Minimum qualifications:

  • Bachelor's degree in Industrial Engineering, Manufacturing Engineering, Mechanical Engineering, Electrical Engineering, Systems Engineering, or equivalent practical experience.
  • 15 years of technical program management, manufacturing engineering, or industrial engineering experience spanning integrated physical/hardware systems.
  • 10 years of experience applying Design for Manufacturing and Assembly (DFM/A), Lean Manufacturing, and process optimization to electromechanical or mission-critical systems.
  • 10 years of experience working directly with external Contract Manufacturers (CMs), Original Design Manufacturers (ODMs), or specialized industrial fabricators to stand up assembly and test lines.

Preferred qualifications:

  • Master’s degree or PhD in Industrial Engineering, Mechanical Engineering, Operations Research, or an MBA with a technical undergraduate degree.
  • 15 years of experience leading industrialization and manufacturing programs for low-to-mid volume, highly complex capital systems (e.g., aerospace systems integration, semiconductor capital equipment, specialized defense systems, complex power/propulsion plants, or modular high-performance compute clusters).
  • Deep technical literacy across both facility infrastructure (structural enclosures, liquid cooling loops, high-power distribution skids) and IT compute hardware (TPU/GPU server trays, rack-level integration, cabling topologies, and L11/L12 assembly).
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