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VP of Engineering, Distributed Storage Services & 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 Distributed Storage Services & 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 influence - shaping direction in close partnership with principal architects - a seat in executive strategy discussions, and a mandate to build and sustain a high-performing engineering organization that can 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.  

What you will 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. 
• Building, developing, and retaining a high-performing, multi-layered engineering leadership team across File, Block, Object, and StorageGRID - with real focus on sustainable team health and long-term retention, not just delivery velocity. 
• 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 - in close partnership with Product Management and principal architects, 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. 
• 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. 

Required 

• 15+ years of engineering leadership in storage, infrastructure, or platform software, including 8+ years leading multiple layers of engineering management, with a track record of building distributed, horizontally scalable, and fault-tolerant systems. 
• 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 with hyperscaler/public-cloud architecture, with a proven track record of deploying large-scale distributed systems. 
• 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. 

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