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.

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.

Job Requirements

• 15+ years of product management experience, including ownership of large‑scale, enterprise‑grade platforms or cloud services.
• Proven track record of defining and scaling AI‑powered products, with hands‑on experience in:
• Generative AI and large language models
• Agentic systems and autonomous workflows
• Retrieval‑Augmented Generation (RAG)
• Model orchestration, evaluation, and lifecycle management
• Enterprise data platforms, vector databases, search, and knowledge graphs
• Demonstrated ability to operate at both strategic and deeply technical levels, bridging executive vision and architectural detail.
• History of influencing VP‑ and C‑level stakeholders through clear product strategy, storytelling, and data‑driven decision‑making.
• Exceptional written and verbal communication skills, with the ability to articulate complex AI concepts to diverse audiences.
• Strong business judgment, systems thinking, and comfort navigating ambiguity at scale.

Education

• MBA or advanced degree in CS/Engineering (helpful, not a substitute for demonstrated technical depth).