About the job

Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. 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 Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. 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 Google Cloud Storage Protocols team plays a central role in maintaining and evolving an architecture and customer-facing API surface. The team maintains and evolves Google Customer Solutions's (GCS) API and its implementation, orchestrating serving path interactions with external services, and driving efforts to unify and simplify serving stacks. As an engineer on the team, you'll play a pivotal role in accelerating AI workloads for customers. You'll do this by designing, implementing, and delivering features that enable products like Rapid Storage. This innovation is a key market differentiator for high-performance storage in AI frameworks.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

The US base salary range for this full-time position is $197,000-$291,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Lead the goal and technical execution to completely rewrite and redesign GCS's next-generation serving stack.

• Drive the design, implementation, and delivery of multi-year customer-facing features, focusing specifically on enabling customers to leverage AI at scale and advancing service availability.

• Act as the technical owner for the most impactful and ambiguous problems within the GCS API space, ensuring high-quality, delivered solutions.

• Provide technical guidance and establish partnerships with engineering teams across Google Cloud to unify serving architectures and solve organizational issues.

• Mentor and develop talented engineers on the team, helping them to grow their careers while successfully working on these ambitious engineering issues.

Minimum qualifications

• Bachelor's degree or equivalent practical experience.

• 8 years of experience in software development.

• 5 years of experience testing, and launching software products.

• 5 years of experience building and developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage, or hardware architecture.

• 3 years of experience with performance tuning or performance optimization.

Preferred qualifications

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.

• 5 years of experience developing cloud-based storage systems.

• Experience building or supporting high-performance Machine Learning infrastructure.

• Experience as a contributor to or maintainer of significant open-source projects, particularly those related to cloud storage, networking, or gRPC/API protocols.

• Experience in caching technologies and data locality optimization in distributed environments.