System Debug Engineer, Cloud AI Infrastructure

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.

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.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $163000 - $237000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Participate in on-call activities and manage domain systems, collaborating with responders to resolve issues.
• Resolve customer issues and troubleshoot AI/ML workloads by developing effective diagnostic and investigation tools.
• Partner with Product, Quality, and SRE teams to improve product quality and production standards.

Minimum qualifications:

• Bachelor's degree in Computer Science or IT-related field, or equivalent practical experience.
  
• 5 years of experience with systems automation, and with systems design and implementation.
  
• 5 years of experience with technical infrastructure (e.g., deployment, maintenance, troubleshooting), and with reliability of technical infrastructure.
  

Preferred qualifications:

• 5 years of experience working with vendors or customers.
• Ability to work as a subject matter expert for stakeholders to resolve complex AI infrastructure obstacles.

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Kirkland, WA, USA; Austin, TX, USA.

In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:

• Health, dental, vision, life, disability insurance
• Retirement Benefits: 401(k) with company match
• Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
• Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
• Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
• Baby Bonding Leave: 18 weeks
• Holidays: 13 paid days per year