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Staff Software Engineer, Site Reliability Engineering

Google · google.com
New YorkLead / Manager8+ yrs
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Subscribers got this job on 23 October 2026. New jobs reach them at 8 am and 6 pm, 5 days before they open here. Get the next one first

The job in short

Site reliability engineering.

Details

Found
5 d ago · posted 2026-10-20
Location as listed
New York, NY, USA
Role
DevOps / SRE / Platform Engineer
Pay (as listed)
$207,000–$300,000 a year
Source
The company’s own careers site

Full description

Site Reliability Engineering (SRE) combines software and systems engineering to build and run large-scale, massively distributed, fault-tolerant systems. SRE ensures that Google Cloud's services—both our internally critical and our externally-visible systems—have reliability, uptime appropriate to customer's needs and a fast rate of improvement. Additionally SRE’s will keep an ever-watchful eye on our systems capacity and performance. Much of our software development focuses on optimizing existing systems, building infrastructure and eliminating work through automation. On the SRE team, you’ll have the opportunity to manage the complex challenges of scale which are unique to Google Cloud, while using your expertise in coding, algorithms, complexity analysis and large-scale system design. SRE's culture of intellectual curiosity, problem solving and openness is key to its success. Our organization 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. Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible. 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 • Engage in and improve the whole life-cycle of services—from inception and design, through to deployment, operation and refinement. • Support services before they go live through activities such as system design consulting, developing software platforms and frameworks, capacity planning and launch reviews. • Maintain services once they are live by measuring and monitoring availability, latency and overall system health. • Scale systems sustainably through mechanisms like automation, and evolve systems by pushing for changes that improve reliability and velocity. • Practice sustainable incident response and blameless postmortems. Minimum qualifications: • Bachelor’s degree in Computer Science, a related field, or equivalent practical experience. • 8 years of experience with software development in one or more programming languages. • 3 years of experience leading projects. • 3 years of experience designing, analyzing, and troubleshooting distributed systems. • 3 years of experienceas a Site Reliability Engineer. • 3 years of experience with software design and architecture. Preferred qualifications: • Master’s degree or PhD in Engineering, Computer Science, or a related technical field. • Experience driving multi-quarter technical roadmaps and influencing engineering direction across multiple partner teams without formal authority. • Demonstrated experience improving service reliability (SLOs/SLIs), capacity planning, and eliminating operational busy work through software engineering and automation. • Expertise in designing, analyzing, and troubleshooting planet-scale distributed storage, serving, or data-processing systems. • Expertise in AI/ML Tools, understanding of their applicability, functionality, and limitations. • Systematic problem-solving approach, coupled with strong verbal and written communication skills and experience mentoring engineers across distributed sites.

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