Google is seeking talented Software Engineers to contribute to the development of cutting-edge technologies that impact billions of users worldwide. This role focuses on creating solutions for massive-scale information processing, encompassing areas like distributed computing, system design, networking, data storage, security, and artificial intelligence. As a Software Engineer, you will engage with diverse projects, adapting to our rapidly evolving business needs and technology landscape. We value versatile individuals with leadership potential, eager to tackle full-stack challenges and drive technological advancements.

You will be an integral part of a dynamic, focused team, responsible for the entire software lifecycle, including design, testing, deployment, and maintenance of innovative solutions.

The AI Data organization is dedicated to accelerating Google's delivery of advanced AI offerings through superior data, robust infrastructure, and sophisticated data science. Within the Trust organization, we are building automated, scalable infrastructure for managing ML assets from development through launch, ensuring full traceability and auditability without hindering developer productivity.

As a PhD Software Engineer, your advanced research expertise will be crucial in addressing complex, real-world challenges on an unparalleled scale.

Take ownership of the design, development, and delivery of key features and components for Google Cloud Platform (GCP) hybrid connectivity products. Lead projects from initial concept through to successful launch with minimal supervision.

Architect and implement highly scalable, reliable, and secure distributed systems tailored for hybrid cloud networking environments. Make critical technical decisions even in ambiguous situations and proactively identify avenues for system enhancements or the creation of new tools.

Foster collaboration with various engineering teams, including Product Management, Site Reliability Engineering (SRE), and other Networking teams within GCP.

Contribute significantly to team-level technical strategy and participate in broader engineering community activities such as candidate interviewing and knowledge sharing initiatives.

Maintain the operational health, monitoring, and on-call support for hybrid connectivity services. Champion efforts to boost system reliability, observability, and supportability, potentially integrating AI/ML for deeper operational insights.

A PhD degree in Computer Science, Electrical Engineering, or a closely related technical discipline is required.

Demonstrated experience in software development, with a focus on large-scale distributed systems, AI/ML, networking, data storage, or security.

Proven experience in architecting and developing distributed systems, including expertise in concurrency, multi-threading, or synchronization.

Solid understanding of algorithms, complexity analysis, and system design principles.

Proficiency in at least one of the following programming languages: C, C++, Python, Java, or Golang.

Preferred qualifications include a PhD in Computer Science or a related technical field, coupled with coding experience in C++/Go. Experience architecting and developing large-scale distributed systems is highly valued. A strong grasp of concurrency, multithreading, and synchronization, along with a deep understanding of networking concepts and protocols (e.g., TCP/IP, BGP), is beneficial. Excellent problem-solving capabilities, a strong understanding of algorithms and their complexity, and adept software and systems troubleshooting/debugging skills are essential. Good written and verbal communication abilities are also expected.