Staff Software Engineer, Infrastructure
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Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience programming in C++.
- 5 years of experience testing, and launching software products.
- 5 years of experience building and developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage, or hardware architecture.
- 3 years of experience with software design and architecture.
Preferred qualifications:
- Experience working on combinatorial optimization problems, advanced graph theory, advanced math and cloud capacity planning.
- Experience building full stack applications including frontend development, backend infrastructure, database design.
- Experience with frontend technologies such as Angular, TypeScript, and reactive programming.
- Experience writing production-grade code using Python, Go and C++.
- Experience in database design and familiarity with data warehousing products such as BigQuery.
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 engineering team develops a multi-layered optimization application to guide long-term infrastructure strategy and asset planning for data centers by balancing trade-offs between land, energy and network costs, along with power availability, network latency, carbon free energy goals, and delivery timelines over a multi-year horizon. The underlying math optimization for supply-demand matching utilizes a combination of evolutionary search algorithms, lexicographic optimization, deterministic multi-step matching heuristics, and mini-max scenario decision theory. Our team also develops tools for Network Demand and Supply Workflows, Energy and Power Forecasting, Agentic Data Lake, Risk management, and Data Analytics. Ours is a high visibility and exponentially growing space. Our optimization products directly inform where Google should make its next-generation data center investments.
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 team 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
- Design and develop software systems to plan Google's long-term infrastructure network through graph modeling and optimization engines to solve complex combinatorial problems.
- Translate complex, abstract mathematical formulations such as combinatorial optimization into clean, robust, and thread-safe production code.
- Architect and develop scalable full stack applications. Design secure web applications using Angular and TypeScript. Design, build, and maintain high-performance backend services using C++, Go, Python.
- Architect and manage data warehousing solutions to store datasets efficiently. Design and optimize database schemas. Build automated pipelines to ingest, transform and aggregate data.
- Own the end-to-end lifecycle of features, including system design, testing, deployment, and monitoring. Promote engineering best practices, including robust design, comprehensive test suite and structured code reviews.
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