Senior Staff AI Data Architect, GKE Storage

Google; Seattle (WA); On-site; USD 262,000 - 364,000; Full time

Benefits offered by this job

Health Insurance

Retirement benefits (401k)

Paid time off (PTO)

Sick time

Maternity/Parental leave

Holiday pay

Job summary

Google in Seattle, WA is seeking a Senior Staff Software Engineer for GKE AI Data to own the data storage and pipelines powering AI/ML workloads on Kubernetes. You will influence architecture, drive cross-team initiatives, and deliver scalable storage across block, file, and object stores.

You will lead and mentor teams, collaborate with GCP storage teams to align strategy, and contribute to industry standards for storage solutions in AI/ML workflows.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 8 years of experience programming in C++.
• 5 years of experience with design and architecture; and testing/launching software products.

Responsibilities

• Guide the architectural direction for GKE AI Data ensuring a scalable, performant and efficient storage solution for AI-ML workloads running on K8s across block, file and object storage.
• Drive storage solutions for evolving AI/ML issues, including KV Caching, fast model loading, and re-envisioning storage for agentic workloads.
• Partner with multiple storage teams in Google Cloud Platform to drive alignment and clarity around strategy and execution.
• Lead the broader Kubernetes ecosystem and Open Source Software community, driving upstream initiatives to establish industry standards for storage solutions.
• Imagine, architect, and lead the technical execution of industry-defining standards through both direct, technical work and by mentoring and guiding teams of engineers.

Education

Bachelor's degree or equivalent practical experience

Tools

C++

Design & Architecture

Testing & Launching Software

Kubernetes OSS

Cross-functional Influence

Job description

Google in Seattle, WA is seeking a Senior Staff Software Engineer for GKE AI Data to own the data storage and pipelines powering AI/ML workloads on Kubernetes. You will influence architecture, drive cross-team initiatives, and deliver scalable storage across block, file, and object stores.

You will lead and mentor teams, collaborate with GCP storage teams to align strategy, and contribute to industry standards for storage solutions in AI/ML workflows.