Senior Staff Software Engineer, NetSoft UTL, Google Global Infrastructure

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.

In this role, you will successfully orchestrate the architecture of large-scale distributed systems at a planetary scale. You will solve algorithmic or data-intensive problems, leading across multiple functional engineering lines, and simplifying legacy infrastructure into modern, scalable automation pipelines.

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: $262000 - $364000 (USD) + 25% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Drive the long-term technical roadmap and system architecture for NetSoft Tier-0 ecosystem, ensuring scalability, reliability, and maintainability across distributed network modeling, planning, and delivery systems.
• Lead the design and evolution of highly distributed, fault-tolerant software infrastructure capable of handling exponential growth in Google’s global network topology and traffic demand.
• Establish standards, guidelines, and unifying architectural principles across multiple complex software stacks to eliminate redundancy, simplify abstractions, and reduce systemic technical debt.
• Apply a systemic focus to architectural decisions, optimizing for global performance, high availability, strict security boundary enforcement, and operational simplicity.

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
  
• 8 years of experience programming in C++.
• 5 years of experience with design and architecture; and testing/launching software products.

Preferred qualifications:

• Experience designing, implementing, and optimizing large-scale, highly available, and fault-tolerant geographically distributed systems.
• Experience coaching, mentoring, and developing executive technical talent, fostering a culture of engineering excellence, design reviews, and shared operational accountability.
  
• Experience driving long-term technical roadmaps and architectural goal across multiple functional engineering teams, converting highly ambiguous, multi-dimensional business requirements into concrete engineering execution pipelines.
• Proven track record of building and operating planetary-scale software infrastructure, with deep expertise in optimizing performance and reliability for algorithmic, graph-based, or highly data-intensive domains.

In most instances, this position requires in-person interviews as part of the hiring process.