Engineering Productivity Lead, Switch Infrastructure
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Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience in software development.
- 2 years of experience in a technical leadership role (e.g., tech lead) driving technical strategy or projects.
- Experience with C++ or Python.
- Experience with Linux networking or embedded systems.
- Experience building and optimizing CI/CD pipelines and build systems (e.g., Bazel, Make).
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- Experience with SONiC, SAI, P4, or open-source networking software stacks.
- Experience managing releases across complex, heterogeneous network switch hardware matrices (Broadcom, Cisco, NVIDIA, Arista).
- Proven track record of applying AI/LLMs to software development workflows, release tooling, or automated testing.
About the job
Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
Deliver high-performance, resilient switch software powering Google's data center and AI infrastructure. Our team is responsible for developing and maintaining the switch operating system deployed in every Google data center. You'll directly contribute to supporting the growth of Gemini and the Google Cloud business, engaging with state-of-the-art technology in hardware (switching ASIC and optics) and software to shape the future of the global network.
In this role, you will build software for switches that power the world's largest AI infrastructure, spanning from data center fabrics to wide area networks and the peering edge of our infrastructure.
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: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Lead and grow an Engineering Productivity team, managing a structure that covers build systems, continuous integration/deployment, testing infrastructure, and release management.
- Optimize development and submit loops to reduce build and test times from hours to minutes and streamline time-to-submit.
- Oversee production switch software releases, qualification gates, branching strategies, and release candidate health metrics.
- Build automated pipelines for continuous downstreaming from open-source repositories and upstream internal improvements.
- Architect and deploy AI-powered automation to eliminate developer toil and accelerate release velocity, collaborating with software simulation for enhanced test selection.
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