Director, Technical Program Management, Manufacturing and Industrial Engineering

Google•Sunnyvale, CA

7d•$281,000 - $391,000

About The Position

The Modular Manufacturing & Integration organization is transforming how Google delivers technical infrastructure for the AI era by industrializing data center delivery through standardized modules and off-site manufacturing. The organization moves assembly, systems integration, and quality testing into controlled factory environments to accelerate delivery of AI compute, liquid cooling, power distribution, and network infrastructure. It defines the modular technical product and is accountable for industrializing and deploying modular capacity globally. The role is described as the Principal TPM of Manufacturing & Industrial Engineering and chief industrial architect for translating Google’s modular infrastructure strategy into executable manufacturing. It bridges design engineering, external contract manufacturing, and on-site field execution, spanning structural modules, medium-to-low-voltage power skids, liquid cooling distribution, and dense AI compute hardware. The role evaluates field deployment and operations bottlenecks and establishes scalable manufacturing processes with global contract manufacturers and fabricators. Its aims are to shorten the time from factory completion to operational AI compute, simplify assembly in factories and in the field, and improve first-pass yield and system quality. The position includes a charter to incubate the discipline and potentially scale a dedicated team over time. The AI and Infrastructure team delivers AI and infrastructure capabilities at scale for Googlers, Google Cloud customers, and Google users. Its work includes AI models, computing infrastructure, TPUs, Vertex AI, Google Global Networking, data center operations, and systems research.

Requirements

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 establish assembly and test lines.

Nice To Haves

Master’s degree or PhD in Industrial Engineering, Mechanical Engineering, or 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, such as aerospace systems integration, semiconductor capital equipment, specialized defense systems, complex power or propulsion plants, or modular high-performance compute clusters.
Deep technical literacy across facility infrastructure, including structural enclosures, liquid cooling loops, and high-power distribution skids, as well as IT compute hardware, including TPU/GPU server trays, rack-level integration, cabling topologies, and L11/L12 assembly.

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, and 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 across Hardware Engineering, Data Center Engineering, and Infrastructure design teams so products are engineered for rapid off-site assembly.
Evaluate on-site data center construction, white-space fit-out, and compute commissioning processes; identify labor-intensive operations and re-engineer them as off-site, factory-integrated steps.