Join Google's pioneering team as a Software Engineer, contributing to the development of cutting-edge technologies that shape how billions interact with information. This role offers the chance to work on projects critical to Google's vast ecosystem, spanning areas like distributed computing, AI/ML, networking, and data storage. You'll have the flexibility to explore diverse challenges and grow with our fast-paced business, requiring versatility, leadership, and a passion for tackling new problems across the full technology stack.

As an integral part of a dynamic and focused team, you will be instrumental in designing, testing, deploying, and maintaining sophisticated software solutions. The AI Data trust organization, specifically, is dedicated to building robust infrastructure for managing ML assets at Google, ensuring traceability and auditability without hindering developer agility.

Leverage your specialized research expertise as a PhD Software Engineer to address complex, real-world challenges at an unprecedented scale. Google Cloud is at the forefront of digital transformation, providing enterprise-grade solutions that empower businesses globally. We seek individuals who can accelerate innovation and solve critical business issues for clients in over 200 countries.

Take ownership of designing, developing, and delivering impactful product features and components within Google Cloud Platform's hybrid connectivity offerings. Drive projects from inception through launch with minimal supervision.

Architect and implement highly scalable, reliable, and secure distributed systems tailored for hybrid cloud networking environments. Exercise sound technical judgment in ambiguous situations and proactively identify opportunities for system enhancements or new tool development.

Foster collaboration across multiple engineering disciplines, including Product Management, Site Reliability Engineering (SRE), and other Networking teams within GCP. Contribute to critical team-level technical decisions and engage in wider engineering community activities such as candidate interviews and knowledge dissemination.

Champion the production health, monitoring, and on-call support for hybrid connectivity services. Lead initiatives to boost system reliability, observability, and supportability, potentially employing AI/ML for advanced operational insights.

A PhD degree in Computer Science, Electrical Engineering, or a closely related technical field is required. You should possess demonstrated experience in software development, with a strong emphasis on large-scale distributed systems, AI/ML, networking, data storage, or security. Expertise in the architecture and development of distributed systems, including proficiency in concurrency, multi-threading, or synchronization, is essential.

Solid experience in algorithms, complexity analysis, and system design is expected. Proficiency in coding within one or more of the following languages is necessary: C, C++, Python, Java, or Golang. Preferred qualifications include a PhD in Computer Science or a related technical field with coding experience in C++/Go, and a proven track record in architecting and developing large-scale distributed systems. A deep understanding of networking concepts, protocols like TCP/IP and BGP, coupled with strong problem-solving, troubleshooting, and debugging skills, will set you apart.