Software Engineering Manager II, Site Reliability Engineering

Site Reliability Engineering (SRE) combines software and systems engineering to build and run large-scale, massively distributed, fault-tolerant systems. SRE ensures that Google's services—both our internally critical and our externally-visible systems—have reliability, uptime appropriate to users' needs and a fast rate of improvement. Additionally SRE’s will keep an ever-watchful eye on our systems capacity and performance.

Our team is dedicated to building and managing the foundational layers that make developer solutions and AI agent platforms reliable, secure, and efficient.

We partner closely with key engineering teams to provide robust support for developer and agent-based workflows across complex hybrid environments—bridging the gap between Google Cloud, production systems, and on-premises infrastructure. By developing and maintaining the automation, rollout, and service management frameworks for internal developer and agentic platforms, we play a vital role in enhancing developer productivity and ensuring seamless service reliability.

• Lead a team of Software/Systems Engineers on projects for users and be directly responsible for uptime.
• Own end-to-end availability and performance of key services and build automation to prevent problem recurrence. Automate response to all non-exceptional service conditions.
• Lead by example, mentor the team and establish credibility through quality technical execution.
• Manage on-call rotations across continents, using a follow-the-sun model.
• Design, write and deliver software to improve the availability, scalability, latency and efficiency of Google's services.

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 managing people or teams.
  
• 3 years of experience leading projects.
  
• 3 years of experience designing, analyzing, and troubleshooting distributed systems.

Preferred qualifications:

• Master's degree in Computer Science or Engineering.
  
• Experience designing and operating developer platforms, sandboxed execution runtimes (e.g., MicroVMs, containers, remote development proxies), or AI coding agent infrastructure at enterprise scale.
• Deep technical expertise in hybrid cloud architectures spanning public cloud primitives (Google Cloud Platform, IAM, GKE/GCE, Terraform/Infrastructure-as-Code) and large-scale internal cluster/container orchestration.