Staff Software Engineer, Site Reliability Engineering

Google•New York, NY

2d•$207,000 - $300,000

About The Position

Site Reliability Engineering (SRE) combines software and systems engineering to build and operate large-scale, massively distributed, fault-tolerant systems. The team ensures Google Cloud services have reliability and uptime appropriate to customer needs while improving them quickly, and monitors system capacity and performance. The work focuses on optimizing existing systems, building infrastructure, and eliminating operational work through automation. The role addresses the scale challenges of Google Cloud using coding, algorithms, complexity analysis, and large-scale system design. The organization emphasizes intellectual curiosity, problem solving, openness, collaboration, self-direction, meaningful projects, and a blame-free environment, with support and mentorship for learning and growth. The role is part of the Technical Infrastructure team, which builds and maintains the infrastructure underlying Google's products, including data centers and Google platforms, and keeps networks running to provide users with a fast, reliable experience.

Requirements

Bachelor’s degree in Computer Science, a related field, or equivalent practical experience.
At least 8 years of experience with software development in one or more programming languages.
At least 3 years of experience leading projects.
At least 3 years of experience designing, analyzing, and troubleshooting distributed systems.
At least 3 years of experience as a Site Reliability Engineer.
At least 3 years of experience with software design and architecture.

Nice To Haves

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, including understanding their applicability, functionality, and limitations.
Systematic problem-solving approach, strong verbal and written communication skills, and experience mentoring engineers across distributed sites.

Responsibilities

Engage in and improve the full life cycle of services, from inception and design through deployment, operation, and refinement.
Support services before launch through system design consulting, development of software platforms and frameworks, capacity planning, and launch reviews.
Maintain live services by measuring and monitoring availability, latency, and overall system health.
Scale systems sustainably through automation and evolve systems through changes that improve reliability and velocity.
Practice sustainable incident response and conduct blameless postmortems.