In most instances, this position requires in-person interviews as part of the hiring process.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 3 years of experience in a technical leadership role; overseeing projects.
- Experience designing, building, and operating large-scale distributed systems, with a focus on scalability, fault tolerance, and reliability.
- Experience designing and developing relational databases, database internals, query processing and query optimization.
- Experience with networking protocols (e.g., TCP/IP, BGP, OSPF), network architectures, or cloud networking services (e.g., VPCs, load balancers, firewalls).
Preferred qualifications:
- Master's degree in Computer Science.
- 10 years of experience in software development.
- 3 years of experience as a team leader or manager with direct reports.
- 3 years of experience working in a complex, matrixed organization.
- Experience in network architecture and common protocols (e.g., TCP/IP, UDP, HTTP, DNS).
- Experience in SQL.
Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way.
With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.
We work closely on ML network designs and are modernizing our infrastructure to address the unique needs of customized whale customer networks, large-scale ML training networks, and accelerated customer support models. On this team, expect to learn about how to scale systems to planet scale, work on agentic systems like Quicksilver, for scaling complex problem solving for a heterogeneous fleet, and understand how a long list of distributed systems work together to make Google's networks work. As a Engineering Manager, you will combine technical leadership and engineering management to oversee mission-critical cluster networks, control plane infrastructure, ML training networks, and next-generation fabric innovations. 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 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.
- Guide the architecture and roadmap for fabric availability, Network Deployment Integration Testing (NDIT) and Machine Learning (ML) fabrics mesh design and development.
- Manage, mentor, and grow a team of high-performing engineers while fostering high-execution culture.
- Drive fabric availability, Service Level Objective (SLO) tracking, automated triaging/root cause analysis, and fabric bandwidth management.
- Manage the team to drive execution on New Product Introductions (NPIs) like DiCoN and virgo mega fabrics, alongside multicast Software Defined Networking (SDN) apps.
- Partner closely with network planning, cloud products, ML infrastructure teams, and system operators to ensure predictable bandwidth and support customized whale customer networks.
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: New York, NY, USA; Sunnyvale, CA, USA.