Minimum qualifications: Bachelor's degree or equivalent practical experience. 8 years of experience in software development. 8 years of experience with one or more general purpose programming languages including: Java, C/C++ or Python. 5 years of experience designing, developing, and launching software products. 5 years of experience building and developing large-scale infrastructure, distributed systems, or large-scale databases systems. 5 years of experience with software design and architecture. 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. 3 years of experience in a technical leadership role leading project teams and setting technical direction. 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects. 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 Network Demand Generation (Demand FA) team is the strategic engine behind NetSoft’s mission to architect Google’s global production network. Our mission is to build the automated systems that translate Google’s product ambitions from Gemini to Cloud into the physical reality of the world’s most sophisticated network infrastructure. As we scale into the AI era, demand financial analysis (FA) is fundamentally rethinking how we plan. We are moving away from process heavy, human-in-the-loop workflows toward a fully autonomous platform. Our software directly dictates billions of dollars in annual capital expenditures (CAPEX) investment, ensuring Google has the capacity to innovate while maintaining optimal cost performance. 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 - $301000 (USD) + 20% bonus target + equity + benefits Learn more about benefits at Google. Responsibilities Drive the technical strategy and architectural goal for critical systems across network product ordering and platform engineering. Lead complex, cross-functional projects from initial design through to launch, ensuring technical excellence and on-time delivery. Mentor and guide other engineers, fostering a culture of high-quality software development and innovation. Collaborate with product managers, program managers, and other engineering teams to define requirements and influence the technical roadmap. Solve challenging problems related to large-scale distributed systems, big data processing, and data repositories.