Site Reliability Engineer Jobs in Sunnyvale, CA

About the job

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.

The Docs SRE team supports the production infrastructure for Google Workspace’s core collaboration products—including Docs, Sheets, and Slides. These universally trusted products rely on Doplar, Google's high-performance real-time collaboration engine. Because billions of users depend on our products to store critical and sensitive data, our primary mission is to ensure this data remains safe, durable, and instantly available. We operate high-throughput, low-latency globally distributed systems, balancing rapid product feature delivery with the uncompromising operational standards required to keep Workspace running seamlessly.

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.

Responsibilities

• Manage the scale and availability of next-generation Workspace GenAI features. We partner with the Workspace AI SRE to support complex agentic flows in Editors, ensuring that model-based features are fast, reliable, and gracefully degrade under load.
• Operate our newly partitioned Spanner storage topology. We have completed the physical isolation of Spanner allocations per Editor and shard, aligning storage failure domains with frontend Pod shards. Focusing on managing elastic resource capacity through auto scaling.
• Orchestrate large-scale, multi-system restore operations for critical customer data. We contribute to tools and playbooks to coordinate data recovery across dependencies, validating data correctness and restoring integrity after complex platform incidents.
• Direct the resource headroom and efficiency roadmap for the Editors portfolio.