Director, Storage Systems Software, Google Platforms Engineering
Google· enterprise· Internet & Cloud Services· Aug 26, 2026 · 2mo agoPosted 62 days ago
Sunnyvale, CA, USA
In office
Full-time
Director
$210K–$270K est.
15+ years exp
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Open 62 days.
Job description
Platforms Engineering performs research, design, and development for the hardware, software, and networking technologies that power all of Google's products and services. The product lines include servers, ASICs, and accelerator systems and storage (e.g., HDDs, SSDs, persistent storage tech, etc.). The customers include Google Cloud Platform (GCP), Ads, Search, YouTube, Gmail, Maps, and more. Platforms offers impactful projects at every level of the technology stack, from the chip level to massive distributed systems design and software development.
In this role, you will manage and build a team of software developers and management leaders at the boundary of hardware/software interaction and upstack innovation with other systems and services like cloud virtualizations, AI/ML applications, and file and object storage.
Additionally, you will be responsible for building storage solutions for all of Google’s services (e.g., Search, Ads, Gmail/Drive, Maps, YouTube, Photos, databases, etc.), AI/ML, and Cloud. The team designs and develops platform software and system designs based on flash, hard disk drives (HDDs), and next-generation disruptive storage technologies.
You will lead innovations and development of various system architectures that will enable us to meet the efficiency challenges of the exponential byte growth and the workloads across all Google AI/ML services, cloud, and virtualized environments. The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.
We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $307000 - $427000 (USD) + 30% bonus target + equity + benefits
Learn more about benefits at Google .
• Be responsible for the roadmap and delivery of the storage systems stack.
• Collaborate with vendors, internal product areas (e.g., Cloud, Search, AI/ML, file/object storage teams, etc.) to enable timely onboarding of new storage systems and a flexible portfolio strategy.
• Manage, lead, and grow a team of system software developers and managers.
• Drive a proactive industry influence agenda towards lowering the barrier of entry to Google Cloud for a wider portfolio of hardware, such as Enterprise.
• Bachelor's degree in Computer Science, Electrical Engineering, related field, or equivalent practical experience.
• 15 years of experience with storage systems.
• 15 years of experience managing teams, including teams with multiple levels.
• Experience working with hardware device suppliers and system vendors.
Minimum qualifications:
• Bachelor's degree in Computer Science, Electrical Engineering, related field, or equivalent practical experience.
• 15 years of experience with storage systems.
• 15 years of experience managing teams, including teams with multiple levels.
• Experience working with hardware device suppliers and system vendors.
Preferred qualifications:
• PhD degree in a field related to computer systems.
• Experience with storage platforms software at hyperscale.
• Experience with cloud virtualization, storage AI/ML needs, and bare metal as a service.
• Experience planning and delivering complex system software.
• Experience delivering storage systems at scale with commercial success.
Application prep
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Keywords to mirror
gcpaimlmachine learning
- Platform
- Effort
- medium