Title:  VP of Engineering, Storage Protocols

Job Summary

VP of Engineering, Storage Protocols 

The Opportunity

Storage is having its moment again — AI training and inference workloads are forcing a rethink of how data is stored, moved, and served at scale, and NetApp sits at the center of that shift. As VP of Engineering for Storage Protocols, you'll own the technical strategy and execution for File (NAS), Block (SAN), and Object (S3) across ONTAP and StorageGRID. Your central mandate is guiding these teams to meet the performance, quality, and scale demands that AI workloads are placing on the protocol stack — from high-concurrency training-data access to inference-time latency and reliability at scale — while keeping the enterprise workloads that are our foundation running without compromise. 

This is a build-and-lead role for someone who wants deep technical ownership at VP scope: real architectural authority, a seat in executive strategy discussions, and a mandate to shape how NetApp's protocol stack evolves to meet the next generation of workloads.

Role:

Reports to: SVP of Platform Engineering 

Location: Remote-friendly — we're flexible on where you're based. Our senior leadership team is primarily based in San Jose, CA, and this role should expect to spend meaningful time there. 

Scope: Leads engineering across File, Block, Object, and StorageGRID protocol teams — an organization of roughly 350 engineers. 

Job Requirements

What You'll Own 

• Technical strategy and execution across ONTAP's File (NFS, SMB, multiprotocol), Block (iSCSI, FC, NVMe/TCP, NVMe/FC), and Object (S3) protocol teams, plus the StorageGRID engineering organization.
• The architectural roadmap for object storage across the portfolio — including how performance-oriented ONTAP S3 and capacity/throughput-oriented StorageGRID object storage differentiate and integrate — partnering closely with Product Management so engineering investment stays coherent rather than duplicative.
• The technical roadmap for multiprotocol data access that balances enterprise workload modernization with emerging AI/ML training, inference, and data-lakehouse use cases.
• Reliability, performance, and scale for the protocol stack, including executive-level ownership of major customer escalations involving protocol behavior at scale.
• Standards participation and protocol compliance (NFS, SMB, iSCSI, FC, NVMe, S3, tables) to keep NetApp interoperable across enterprise and hyperscaler ecosystems.
• Organizational design for where protocol and control-plane capabilities sit within Platform Engineering — grounded in evidence like backlog composition and ownership boundaries.
• Building and retaining a high-performing, multi-layered engineering leadership team across File, Block, Object, and StorageGRID.
• Close partnership with peer engineering leaders across ONTAP Core, Manageability, and Data Replication (MetroCluster, SnapMirror) to keep the broader storage platform architecturally coherent.
• A voice in executive technical strategy, including NetApp's technical narrative on object and metadata architecture for neocloud customers.  

What We're Looking For  

Required 

• 15+ years of engineering leadership in storage, infrastructure, or platform software, including 8+ years leading multiple layers of engineering management. 
• Deep technical fluency in enterprise distributed systems — e.g., storage protocols (NAS, block, or object/S3), large-scale networking, or comparable infrastructure domains — with the ability to go deep on at least one and reason credibly across the others. 
• A track record of resolving ambiguous, cross-organizational architectural and org-design questions, and of leading large-scale customer escalations to resolution across engineering, support, and field teams. 
• Excellent executive communication — you can represent complex technical tradeoffs clearly to senior leadership and partner effectively with Product Management. 

Strongly Preferred 

• Experience building storage or data infrastructure for AI/ML workloads — training, inference, or data pipelines. 
• Experience restructuring or right-sizing engineering teams based on evidence rather than assumption. 
• A leadership style grounded in developing others, not positional authority. 

Education

Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field.