Own Every Moment at NetApp
At NetApp, your ideas power innovation. We lead in intelligent data infrastructure—delivering unified storage, integrated data services, and solutions that help organizations unlock the full potential of their data, from AI to multicloud.
Ready to innovate and contribute to our path to $10B? Here, you'll collaborate with passionate teams, tackle real-world challenges, and see your impact in how customers transform and grow. If you're ready to bring curiosity, creativity, and drive to every moment, NetApp is where your journey begins. Join teams that innovate to elevate, drive results, and excel together across every function.
The NetApp’s Cloud Storage & Services division is responsible for delivering industry‑leading storage and data platforms that power mission‑critical enterprise workloads. Our portfolio spans cloud storage services, deep integrations with hyperscaler AI/ML ecosystems, and AI‑native services that enable Fortune 500 customers to operationalize data and AI across hybrid and public cloud environments.
We are seeking a Principal Product Manager — the most senior individual contributor product role at NetApp — to define and drive the long‑term strategy, architecture, and execution of generative and agentic AI platforms. This role is reserved for a recognized product leader who operates with company‑level strategic impact, demonstrates deep technical credibility, and shapes outcomes across multiple teams, product lines, and executive stakeholders.
As a Principal PM, you will set the multi‑year vision for AI‑powered services built on NetApp’s data infrastructure, guide complex cross‑portfolio initiatives, and serve as a thought leader for enterprise‑grade agentic systems, LLM‑based platforms, and AI‑driven user experiences. While this is an individual contributor role, your influence will extend broadly across engineering, research, design, go‑to‑market, field teams, partners, and executive leadership.
AI strategy & roadmap
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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.
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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:
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Training and inference data planes (high throughput, low latency, checkpointing, bursty I/O)
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RAG and enterprise search (datasets, versioning, clones, refresh patterns)
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Agentic workflows and orchestration (durable shared state, tool/data access patterns—where productized responsibly)
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Large multimodal and enterprise datasets (governance, access control, lifecycle)
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Analytics and simulation adjacencies (HPC/EDA-style throughput, shared filesystem semantics)
Hyperscaler & ecosystem partnership
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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.
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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
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Lead across engineering, product marketing, sales, customer success, and professional services to ship capabilities and repeatable reference architectures / proof points.
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Engage strategic customers and design partners to validate pain, quantify value, and de-risk roadmap bets.
Market intelligence & evangelism
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Monitor AI infrastructure trends (models, frameworks, orchestration, data formats) and competitor moves; translate into differentiated bets.
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Represent ANF as a credible technical executive in briefings, advisory councils, and industry forums.
Industry segmentation
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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.
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15+ years of product management experience, including ownership of large‑scale, enterprise‑grade platforms or cloud services.
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Proven track record of defining and scaling AI‑powered products, with hands‑on experience in:
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Generative AI and large language models
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Agentic systems and autonomous workflows
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Retrieval‑Augmented Generation (RAG)
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Model orchestration, evaluation, and lifecycle management
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Enterprise data platforms, vector databases, search, and knowledge graphs
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Demonstrated ability to operate at both strategic and deeply technical levels, bridging executive vision and architectural detail.
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History of influencing VP‑ and C‑level stakeholders through clear product strategy, storytelling, and data‑driven decision‑making.
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Exceptional written and verbal communication skills, with the ability to articulate complex AI concepts to diverse audiences.
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Strong business judgment, systems thinking, and comfort navigating ambiguity at scale.
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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.
Submitting an Application
To ensure a streamlined and fair hiring process for all candidates, our team only reviews applications submitted through our company website. This practice allows us to track, assess, and respond to applicants efficiently. Emailing our employees, recruiters, or Human Resources personnel directly will not influence your application.
AI Disclosure
For select roles, some stages of our hiring process may use artificial intelligence tools to help evaluate applications and candidate selection. These tools support—rather than replace—human decision-making.
