Software Engineer III, Reliability Infrastructure, Workspace Platform

Google•Durham, NC

1d•$147,000 - $210,000

About The Position

Google software engineers develop technologies that serve billions of users and handle information at massive scale. This role works on a project critical to Google, with opportunities to take on new problems across the full stack as the business evolves. The Workspace Platform Reliability Infrastructure team aims to ensure Workspace resilience through zero-touch, automated infrastructure for continuous data recovery validation and proactive dependency risk assessment. The team builds infrastructure for automated data recovery testing, fault-injection pipelines, and dependency detection systems that provide engineers with actionable product stability insights. Its infrastructure simulates users across different operational scales to model Workspace customers, and the team collaborates closely with first-party application teams and SREs to build unified capabilities across Workspace. The role supports Google Workspace products and their evolving AI capabilities, with the opportunity to work with Google DeepMind model builders and affect users globally. Individual compensation depends on job-related skills, experience, and relevant education or training. The listed U.S. compensation is $147,000–$210,000, plus a 15% target bonus, equity, and benefits.

Requirements

Bachelor’s degree or equivalent practical experience.
2 years of experience with software development in one or more programming languages, such as Java or C++.
2 years of experience building and managing distributed software systems and infrastructure.
2 years of experience testing and launching software products, and building developer tools that improve developer velocity, code quality, and code health.

Nice To Haves

Master’s degree or PhD in Computer Science or a related technical field.
2 years of experience with data structures and algorithms in an academic or industry setting.
2 years of experience with performance, large-scale systems data analysis, visualization tools, or debugging.
2 years of experience with chaos engineering, using fault-injection frameworks to simulate failure scenarios.
2 years of experience with synthetic data generation and managing pipelines for processing or transferring large datasets.

Responsibilities

Write product or system development code.
Build internal software products to validate, measure, and report end-to-end Time to Recovery (TTR) for data restore scenarios on an ongoing basis.
Lead and manage large-scale data seeding pipelines for realistic disaster recovery testing and performance validation across Workspace applications.
Maintain high engineering standards through comprehensive test coverage, clear documentation, effective monitoring, and strong debuggability.
Provide automated solutions that help Workspace apps remain resilient to dependency failures by accurately classifying hard and soft dependencies.
Understand stakeholder requirements and translate them into robust software solutions.