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.

Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.

The AI and Infrastructure team works on the world’s toughest problems, redefining what’s possible and the possible easy. We empower Google customers by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Googler Cloud customers, and billions of Google users worldwide. We’re at the center of amazing work at Google by being the “flywheel” that enables our advanced AI models, delivers computing power across global services, and offers platforms that developers use to build services.

In AI and Infrastructure, we shape the future of hyperscale computing by inventing and creating world-leading future technology, and drive global impact by contributing to Google infrastructure, from software to hardware (including building Vertex AI for Google Cloud). We work on complex technologies at a global scale with key players in the AI and systems space. Join a team of talented individuals who not only work together to keep data centers operating efficiently but also create a legacy of driving innovation by building some of the most complex systems technologies.

The US base salary range for this full-time position is $141,000-$202,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Write product or system development code.

• Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.

• Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).

• Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.

• Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.

Minimum qualifications

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience programming in C++, Python or Go.
• 2 years of experience with developing large - scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture.

Preferred qualifications

• Master's degree or PhD in Computer Science or related technical fields.

• 2 years of experience with performance, large scale systems data analysis, visualization tools, or debugging.

• 2 years of experience with data structures or algorithms in either an academic or industry setting.

• Experience developing accessible technologies.

• Proficiency in code and system health, diagnosis and resolution, and software test engineering.