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.
Distributed and Sovereign Cloud (DSC) brings the power of Google Cloud to any environment whether in a central data center, at the edge, or completely in the cloud. Within this ecosystem, the Storage Everywhere team builds solutions that allow stateful applications to run seamlessly across all of these environments. The DSC File and Block Storage Team is a critical pillar of the DSC air-gapped portfolio. The team ensures that highly secure, disconnected environments have access to robust, high-performance, and secure storage services.
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.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $207000 - $301000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Drive core file and block features within the DSC air-gapped ecosystem. Define and optimize storage performance utilizing tools to meet strict input/output operations per second (IOPS), throughput, and latency benchmarks aligned with Google Cloud best practices.
- Enhance observability, monitoring, and automated remediation to ensure high availability. Implement secure, multi-tenant environments leveraging virtual machines.
- Architect storage solutions to support advanced AI/ML workloads. Collaborate across organizations to ensure overall DSC architecture scales effectively.
- Mentor engineers, establish robust software development governance, and leverage AI tooling to accelerate developer velocity.
Qualifications
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 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.
- 4 years of experience designing, implementing, and optimizing enterprise-grade file and block storage architectures.
- 3 years of experience with software design and architecture.
- 3 years of experience with storage performance characterization, throughput benchmarking, or latency optimization using industry-standard tools.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 8 years of experience with data structures and algorithms.
- 3 years of experience in a technical leadership role leading project teams and setting technical direction.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
- 3 years of experience with NetApp ONTAP architecture, including configuring storage virtual machines and multi-tenant role-based access control.
- 2 years of experience designing high-throughput, low-latency storage architectures optimized for scaling AI/ML workloads or air-gapped systems.