Software Engineer III, Reliability Infrastructure, Workspace Platform

About the role

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.

ABOUT THE JOB:

Google's software engineers develop the next-generation technologies that change

how billions of users connect, explore, and interact with information and one

another. Our products need to handle information at massive scale, and extend

well beyond web search. We're looking for engineers who bring fresh ideas from

all areas, including information retrieval, distributed computing, large-scale

system design, networking and data storage, security, artificial intelligence,

natural language processing, UI design and mobile; the list goes on and is

growing every day. As a software engineer, you will work on a specific project

critical to Google’s needs with opportunities to switch teams and projects as

you and our fast-paced business grow and evolve. We need our engineers to be

versatile, display leadership qualities and be enthusiastic to take on new

problems across the full-stack as we continue to push technology forward.

Our mission is to ensure Workspace resilience by providing zero-touch, automated

infrastructure for continuous data recovery validation and proactive dependency

risk assessment.

We proactively identify and mitigate risks by building infrastructure for

automated data recovery testing, fault-injection pipelines, and dependency

detection systems that give engineers actionable insights into product

stability.

Simulating users across various operational scales, our infrastructure is

expected to model the various customer landscape of Workspace. Our team

maintains ongoing, close collaboration with first-party application teams and

SREs to cultivate unified platform capabilities across the entire Workspace

suite.

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

[https://www.google.com/about/careers/applications/benefits/].

RESPONSIBILITIES:

• 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.