Netapp Marketing Jobs (NOW HIRING)

If you're ready to bring curiosity, creativity, and drive to every moment, NetApp is where your journey begins. Job Summary NetApp is hiring a principal-level product leader to own the AI product strategy for Azure NetApp Files (ANF)—a first-party, fully managed enterprise file service on Microsoft Azure, delivered in deep partnership between NetApp and Microsoft. In the spirit of NetApp's \"business builder\" cloud roles, you will translate a fast-moving AI landscape into differentiated platform capabilities, joint roadmap bets with Microsoft, and enterprise outcomes (performance, data locality, governance, and time-to-value for AI pipelines). You will sit at the intersection of enterprise storage, Azure AI infrastructure, and industry AI workloads, ensuring ANF is positioned and built as a strategic data foundation for training, inference, RAG, analytics, simulation, and agentic workflows—without forcing customers to abandon enterprise file semantics, protection, or hybrid operating models. Role Overview We need a highly strategic and deeply technical principal PM who can: * Define multi-year AI vision and roadmap for ANF in the context of Azure AI services, GPU estates, data platforms, and regulated enterprise environments. * Turn emerging patterns (LLMs, RAG, agents, orchestration, multimodal data, vector retrieval, high-throughput checkpointing) into concrete product requirements and joint go-to-market narratives with Microsoft. * Balance hyperscaler co-development constraints with NetApp differentiation (enterprise data services, multiprotocol access, lifecycle management, resiliency, and cross-cloud consistency where relevant). Responsibilities AI strategy & roadmap * Own end-to-end AI strategy for ANF: problem selection, success metrics, phased delivery, and competitive positioning vs. other Azure and AI-native storage options. * Prioritize investments across performance, scale, data services, protocol and API surfaces, and operational excellence for AI pipelines. Workload-led product definition Drive requirements for AI-centric scenarios, including: * Training and inference data planes (high throughput, low latency, checkpointing, bursty I/O) * RAG and enterprise search (datasets, versioning, clones, refresh patterns) * Agentic workflows and orchestration (durable shared state, tool/data access patterns—where productized responsibly) * Large multimodal and enterprise datasets (governance, access control, lifecycle) * Analytics and simulation adjacencies (HPC/EDA-style throughput, shared filesystem semantics) Hyperscaler & ecosystem partnership * Partner with Microsoft teams across Azure AI / Foundry, Azure Machine Learning, AKS / container platforms, GPU infrastructure, data/analytics (e.g.

Databricks-style patterns on Azure), and core Azure storage/networking dependencies. * Align ANF's AI story with Azure-wide AI data guidance and reference architectures, and feed real customer workload evidence back into joint planning. Cross-functional leadership * Lead across engineering, product marketing, sales, customer success, and professional services to ship capabilities and repeatable reference architectures / proof points. * Engage strategic customers and design partners to validate pain, quantify value, and de-risk roadmap bets. Market intelligence & evangelism * Monitor AI infrastructure trends (models, frameworks, orchestration, data formats) and competitor moves; translate into differentiated bets. * Represent ANF as a credible technical executive in briefings, advisory councils, and industry forums. Industry segmentation * Tailor AI storage strategy for segments where file semantics and performance matter, for example: semiconductor/EDA, manufacturing, healthcare imaging, financial services, energy, media & entertainment, and HPC/simulation—including compliance and data residency realities. AI strategy & roadmap * Own end-to-end AI strategy for ANF: problem selection, success metrics, phased delivery, and competitive positioning vs. other Azure and AI-native storage options. * Prioritize investments across performance, scale, data services, protocol and API surfaces, and operational excellence for AI pipelines. Workload-led product definition Drive requirements for AI-centric scenarios, including: * Training and inference data planes (high throughput, low latency, checkpointing, bursty I/O) * RAG and enterprise search (datasets, versioning, clones, refresh patterns) * Agentic workflows and orchestration (durable shared state, tool/data access patterns—where productized responsibly) * Large multimodal and enterprise datasets (governance, access control, lifecycle) * Analytics and simulation adjacencies (HPC/EDA-style throughput, shared filesystem semantics) Hyperscaler & ecosystem partnership * Partner with Microsoft teams across Azure AI / Foundry, Azure Machine Learning, AKS / container platforms, GPU infrastructure, data/analytics (e.g. Databricks-style patterns on Azure), and core Azure storage/networking dependencies. * Align ANF's AI story with Azure-wide AI data guidance and reference architectures, and feed real customer workload evidence back into joint planning. Cross-functional leadership * Lead across engineering, product marketing, sales, customer success, and professional services to ship capabilities and repeatable reference architectures / proof points. * Engage strategic customers and design partners to validate pain, quantify value, and de-risk roadmap bets. Market intelligence & evangelism * Monitor AI infrastructure trends (models, frameworks, orchestration, data formats) and competitor moves; translate into differentiated bets. * Represent ANF as a credible technical executive in briefings, advisory councils, and industry forums. Industry segmentation * Tailor AI storage strategy for segments where file semantics and performance matter, for example: semiconductor/EDA, manufacturing, healthcare imaging, financial services, energy, media & entertainment, and HPC/simulation—including compliance and data residency realities. Job Requirements Required * 10+ years product management in cloud infrastructure, enterprise storage, AI/ML infrastructure, or data platforms (principal scope: portfolio strategy, multi-team alignment, executive storytelling). * Strong command of enterprise storage: NFS/SMB semantics, snapshots/clones, replication, backup integration patterns, capacity/performance tiers, and large-scale filesystem behavior under parallel workloads. * Hands-on familiarity with modern AI stacks: LLMs, RAG architectures, embeddings/vector retrieval patterns, training vs.

inference IO profiles, orchestration, and enterprise AI data pipelines. * Demonstrated success influencing engineering and partner roadmaps without direct authority; experience with hyperscaler first-party or deeply partnered services is a strong plus. * Excellent written and verbal communication to customers, executives, and engineers. Preferred * Direct experience with Microsoft Azure AI services, GPU estates on Azure, and/or Azure Kubernetes Service + ML platform integrations. * Familiarity with Databricks, Iceberg/Delta-class open table patterns, Kubernetes storage patterns, NVIDIA AI software stacks, and enterprise MLOps release cadences. * Background in regulated industries and enterprise security/governance requirements for AI data. Education * MBA or advanced degree in CS/Engineering (helpful, not a substitute for demonstrated technical depth). Compensation: The target salary range for this position is $228,000 - $325,000. The salary offered will be determined by the candidate's location, qualifications, experience, and education and may be outside of this range. Final compensation packages are competitive and in line with industry standards, reflecting a variety of factors, and include a comprehensive benefits package.

This may cover Health Insurance, Life Insurance, Retirement or Pension Plans, Paid Time Off, various Leave options, Performance-Based Incentives, employee stock purchase plan, and/or restricted stocks (RSU's), with all offerings subject to regional variations and governed by local laws, regulations, and company policies. Benefits may vary by country and region, and further details will be provided as part of the recruitment process. At NetApp, we embrace a hybrid working environment designed to strengthen connection, collaboration, and culture for all employees. This means that most roles will have some level of in-office and/or in-person expectations, which will be shared during the recruitment process. Equal Opportunity Employer: NetApp is firmly committed to Equal Employment Opportunity (EEO) and to compliance with all federal, state and local laws that prohibit employment discrimination based on age, race, color, gender, sexual orientation, gender identity, national origin, religion, disability or genetic information, pregnancy, protected veteran status, and any other protected classification. Why You'll Thrive at NetApp At NetApp, you won't wait for the perfect moment—you'll make it.

The early planning, the extra thought, the bold idea that turns good into great: That's how our people operate and how we continue to push the boundaries of data infrastructure. NetApp is the trusted partner for organizations transforming data into opportunity. As the only enterprise-grade storage service natively embedded in Google Cloud, AWS, and Microsoft Azure, we empower customers to run everything from traditional workloads to enterprise AI with unmatched performance, resilience, and security. Our culture We celebrate mold breakers, bold thinkers, and problem solvers. We reward initiative, impact, and ownership.

We provide flexibility so you can balance professional ambition with your personal life. Here, differences are not just welcomed—they drive everything we do. If you're ready to innovate, rise to the challenge, and own every moment - make your next move your best one. Apply now.