Principal Engineer, Global Network Core, Google Cloud

Minimum qualifications:

• Bachelor's degree in Computer Science, Engineering, a related technical field, or equivalent practical experience.
• 15 years of professional experience in software engineering.
• Experience with technical innovation in Infrastructure networking domain.

Preferred qualifications:

• Master's degree or PhD in Computer Science or a field related to Networking or Networked Systems.
• Understanding of the latest AI and ML capabilities.
• Ability to influence and lead without direct authority, building strong relationships and driving alignment across teams.
• Ability to upskill teams and integrate AI-driven solutions to improve large-scale systems such as reducing capacity delivery lead times, improve testing coverage, etc.
• Exceptional communication skills, including ability to articulate complex technical concepts to both engineering leaders and non-technical stakeholders.
• Proven track record of leading and delivering large-scale, complex network or networked infrastructure transformations from concept to deployment.

About the job

As a Principal Software Engineer for Global Network Core (GNC), you will pioneer the technological vision for a critical mandate. You will discover the defining technologies and forge the architectural path for Google’s planet-scale Wide Area Network (WAN), ultimately empowering our largest, most demanding internal and external AI/ML customers with a backbone network engineered for unmatched performance.

In this role, you will make high-stakes technical architecture decisions and deep-dive into complex distributed systems and network operations. You will navigate extreme scale and ambiguity, driving cross-functional alignment across AI2 and DeepMind. In addition, you will not only ensure our network foundation stays ahead of explosive capacity demands, but also build the most optimal, high-performance network to power AI training and inference. By acting as a pivotal liaison between Google's internal engineering and broader academic and industry research communities, you will guarantee our architecture continuously outpaces industry standards.

To be effective in this role, you must seamlessly flex between technical depth and broad strategic influence. You will be expected to foster a welcoming environment by treating everyone with respect and actively seeking out perspectives, especially during complex architectural disagreements. You must be a highly dependable teammate, taking full responsibility for the success and failure of these critical systems, and delivering high-quality work aligned with our hybrid, three-day-a-week in-office model. Finally, you must collaborate effectively—communicating clearly, identifying conflicting goals across partner organizations, and proactively finding ways to increase alignment to arrive at the best collective outcomes for Google.

Google 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.

The US base salary range for this full-time position is $307,000-$427,000 + 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 design of our new WAN for AI, defining a multi-year engineering roadmap to deliver 100x more network capacity for explosive AI/ML demand growth.
• Leverage deep technical knowledge across the full network stack—spanning physical topology design, vendor strategy, global traffic engineering, routing device control, and rigorous security and safety protocols.
• Partner across AI & Infrastructure (AI2) and DeepMind to define a core network product portfolio that meets both AI training and inference needs for internal and external customers.
• Ensure the new network integrates seamlessly with vertical AI stacks (TPU, LLMs, JAX/XLA) to dramatically improve performance while driving down unit costs and deployment lead times for our planning and design partners.
• Collaborate with academic institutions and industry pioneers to anticipate technology trends, translating external innovations into significant, long-term competitive advantages for Google's network.