AI will change the future of work in profound ways, and our products— Gmail, Docs, Drive, Calendar, Sheets, Vids and Meet are at the forefront. From pre-computed summaries for email threads, summaries for meetings, and videos created from a document using lifelike AI avatars, our AI opportunity is huge. Our mission is to meaningfully connect people so they can create, build, and grow together and as part of the team you can build how productivity tools should work 5-10 years into the future. You will work with model builders (Google DeepMind), work with exceptional leaders, and have the ability to impact billions of users across the world.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Write product or system development code.
Build internal software products to validate, measure and report Time to Recovery (TTR) end-to-end for various data restore scenarios on an ongoing basis.
Lead and manage large-scale data seeding pipelines to support realistic disaster recovery testing and performance validation across Workspace applications.
Ensure all work upholds high standards of engineering excellence, including comprehensive test coverage, clear documentation, effective monitoring, and strong debuggability.
Provide automated solutions to ensure Workspace apps remain resilient to dependency failures by accurately classifying hard vs soft dependencies and understand and translate stakeholder requirements into robust software solutions.
Minimum qualifications
Bachelor’s degree or equivalent practical experience.
2 years of experience with software development in one or more programming languages (e.g., Java and C++).
2 years of experience building and managing distributed software systems and infrastructure.
2 years of experience testing, launching software products, and building developer tools that improve developer velocity, code quality and code health (e.g., compilers, automated releases, code design and testing, test automation frameworks).
Preferred qualifications
Master's degree or PhD in Computer Science or related technical fields.
2 years of experience with data structures and algorithms in either an academic or industry setting.
2 years of experience with performance, large-scale systems data analysis, visualization tools, or debugging.
2 years of Chaos engineering, using fault injection frameworks to simulate failure scenarios.
2 years of experience with synthetic data generation, managing pipelines for processing or transferring large datasets.
Bachelor’s degree or equivalent practical experience.
2 years of experience with software development in one or more programming languages (e.g., Java and C++).
2 years of experience building and managing distributed software systems and infrastructure.
2 years of experience testing, launching software products, and building developer tools that improve developer velocity, code quality and code health (e.g., compilers, automated releases, code design and testing, test automation frameworks).
