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# Technical Program Manager, Enterprise Network Infrastructure Design

- **Company:** Google LLC
- **Location:** Austin, TX, United States
- **Experience:** Expert
- **Salary:** $163,000 - $236,000
- **Contract:** Permanent contract
- **Skills:** Computer-Aided Design, AutoCAD, Artificial Intelligence, Autodesk Revit, Computer Networks, Data Centers, Machine Learning, Information Technology, Machine Learning Operations
- **Published:** November 3, 2026
- **Apply:** https://dejobs.org/x/x/CF33A8D0FF8D4212B574A20B01A70566/job/

## About the Role

Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area., * Bachelor's degree in a technical field, or equivalent practical experience.

 * 5 years of experience in program management.
 * Experience with data center physical infrastructure design, construction, or deployment.
 * Experience working at a cloud hyperscaler., * Bachelor's in Mechanical, Electrical, Industrial Engineering, Computer Science, or equivalent practical experience.
 * 7 years of experience as a technical program manager leading brownfield retrofits and high-density AI/ML infrastructure deployments.
 * 5 years of experience in technical program management, data center design, or critical facilities construction.
 * Experience managing space, power, and cooling constraints, and analyzing CAD/BIM layouts.
 * Experience with AutoCAD/Revit and leveraging AI/ML technologies for workflow automation.
 * Deep knowledge of low-voltage power, liquid cooling (CDUs/manifolds), and optical fiber systems.

## Description

* Lead complex greenfield and brownfield server hall layout programs. Translate ambiguous 6+ month goals into clear phases, OKRs, and milestones from initial feasibility through 30/65/90% design gates to Issue for Construction (IFC).
 * Lead cross-functional engineering reviews across MEP, structural loading, busway power, liquid cooling (CDUs/manifolds), and fiber conveyance to resolve topological trade-offs and de-risk deployments.
 * Drive program pivots and modernizations for in-flight ML design modifications. Author impact analyses, CAD redlines, and technical SOWs, structuring workflows for less senior team members.
 * Align executive leaders in capacity, networks, facilities, and supply chain on multi-year roadmaps and capacity sequencing. Establish program governance and leverage AI/ML to automate spatial planning and layout validation.