Senior Product Engineer, Global Manufacturing Engineering

Senior Product Engineer, Global Manufacturing Engineering

_corporate_fare_ Google _place_ Atlanta, GA, USA

** Mid*
* Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.

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* Minimum qualifications:

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* + Bachelor's degree in Computer Science, Electrical Engineering, Mechatronics, a related technical field, or equivalent practical experience.

+ 8 years of experience in manufacturing.

+ 8 years of experience in product engineering, manufacturing or development management.

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* Preferred qualifications:

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* + Master's degree or Doctor of Philosophy (PhD) in Electrical, Mechanical, Industrial, Materials, or a related engineering field.

+ 10 years of experience in product engineering, manufacturing or development management.

+ Experience developing and integrating manufacturing hardware using custom electronics, specialized fixturing, and instrumentation in collaboration with global contract manufacturing partners.

+ Experience in technical leadership roles and project management, with the ability to manage complex initiatives and deliver clear executive-level communication.

** About the job*
* Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.

As a Senior Product Engineer, you will serve as the strategic technical lead architecting the transition from design to global manufacturing for Google's next-generation data center infrastructure. You will own the technical roadmap for platform deployment, spanning servers, storage, and accelerators, by defining Design for Manufacturing standards and steering the manufacturing strategy that enables Google to scale with unrivaled speed and precision.

You will act as the authority on hardware lifecycle health, moving beyond reactive troubleshooting to proactively drive systemic improvements in yield, test coverage, and operational efficiency. By leading complex root-cause investigations into global field escapes and influencing upstream design changes, you will bridge the gap between internal engineering and global partners to ensure our infrastructure remains the most reliable and cost-effective architecture in the world.

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 team 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.

The US base salary range for this full-time position is $144,000-$209,000 + 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*
* + Lead the end-to-end build, optimization, and deployment of high-complexity data center hardware platforms, including servers, storage, switches, racks, and accelerators, across…