Senior Systems Development Engineer, Google Cloud

1 Month ago • 5 Years + • DevOps

Job Summary

Job Description

As a Senior Systems Development Engineer at Google Cloud, you'll manage services and systems at scale, automating tasks and developing tools to solve problems. You'll work with server and service owners to ensure the reliability and sustainability of Google's infrastructure, supporting physical, virtual, and cloud servers. Responsibilities include problem-solving in Linux internals or cloud APIs, architecting and developing scalable tools, and owning and supporting Google's server infrastructure and cloud environments. The role involves collaborating with a team to build infrastructure, tools, and telemetry for Google-scale service orchestration.
Must have:
  • Bachelor's degree in CS or related field
  • 5+ years systems administration/development experience
  • 5+ years scripting (Python/Go) and automation experience
  • 5+ years network administration/troubleshooting experience
  • Own and support Google's server infrastructure
  • Develop scalable and maintainable solutions
Good to have:
  • Experience with Go or Python coding projects (distributed systems)
  • Networking, storage, monitoring experience

Job Details

Minimum qualifications:

  • Bachelor's degree in Computer Science or IT-related field, or equivalent practical experience.
  • 5 years of experience with systems administration, systems development engineering, or similar roles.
  • 5 years of experience with scripting, automation in Python or Go.
  • 5 years of experience in network administration or network troubleshooting.

Preferred qualifications:

  • Experience in one of the following areas: coding projects (potentially including distributed systems) in Go or python, networking, storage, monitoring.

About the job

Systems Development Engineering (SDE) at Google is a role where you manage services and systems at scale. SDEs creatively put their engineering discipline to use automating the mundane and reducing toil. We don’t just write code to fix bugs, but emphasize the development of tools and solutions that fix classes of problems. We know it’s hard to control what you can’t measure – so we focus on observability: instrumenting first, then turning data into knowledge, and finally knowledge into action. We know that the operational efficiency of Google systems, services, virtual compute environments and the operating systems that power them impact the environment, not just the bottom line. We know that working together we can do more, and that community matters.

Google brings together people with a wide variety of backgrounds, experiences and perspectives. We encourage them to collaborate, think big and take risks in a blame-free environment. We promote self-direction to work on meaningful projects, while we also strive to create an environment that provides the support and mentorship needed to learn and grow.

Together we engineer and build the infrastructure, tools, access and telemetry for systems that enable orchestration of Google-scale services. Come build things that matter.

The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.

We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.

Responsibilities

  • Own and support the needs of one of Google's server infrastructure and cloud environments.
  • Work with other server and service owners to ensure the continued expansion, reliability, and sustainability of the Google service infrastructure.
  • Support physical, virtual, and cloud servers in a subjective environment.
  • Solve problems in Linux internals or cloud Application Programming Interface (APIs).
  • Architect and develop tools with a focus on elegant, scalable, and maintainable solutions.

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