Staff Software Engineer, Core Systems and Capacity Assurance
Confirmed on the employer's own hiring board on Oct 20, 2026. First seen by Alion on Oct 12, 2026. Google scores B on the Alion truth index.
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.
The Core Systems and Capacity Assurance (CSCA) Team is responsible for the journey of a new system from the point of manufacturing to data center delivery. We do this on projects that push the limits of technologies and provide you with an opportunity to make a broad impact across all of Google's product families. The technologies include systems that support machine learning, video transcoding, security, general compute, image processing, and storage. You will be a part of the new emerging technologies and systems that push the limits of computation. Please note this position requires about 20% Travel to Google Data Centers primarily in US, and also to Manufacturing CM partner sites in US, Mexico, and possibly Asia.
The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.
We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Manage the development of automation, processes, and diagnostics in support of new product introduction to enable the efficient installation, configuration, testing and management of new data center hardware from the time of manufacturing to installation.
- Develop new product test solutions, and will work closely with our hardware and software partner teams to ensure that the end to end data center automated diagnosis and repair systems are working efficiently and integrated properly with the signals generated from our test infrastructure and diagnostics.
- Develop software that executes in thousands of systems in parallel and develop the data insights required to analyze the complex result sets, and optimize repair strategies for fault coverage and fault isolation.
- Manage the new product introduction process to ensure that new hardware platforms turn up from manufacturing to our data centers.
Qualifications
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience testing, and launching software products.
- Experience integrating generative AI tools or LLM interfaces into workflows.
- Experience in data analysis, test automation, failure analysis and embedded systems.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 8 years of experience with data structures and algorithms.
- Experience in data center systems, linux, data center networking, machine automation, ML hardware, and strong debugging and technical troubleshooting skills.