About the Job
As a Senior Product Marketing Manager at vCluster Labs, you aren't just supporting launches from the sidelines; you are the founding product marketer for a company that turns raw GPU infrastructure into usable cloud platforms. We enable cloud providers and enterprises to offer what the hyperscalers offer: managed Ku...
As a Senior Product Marketing Manager, your role will include:
Messaging and positioning: Build clear, differentiated messaging for the vCluster product stack (vCluster, vMetal, vCluster Platform) in the cloud-native ecosystem, and align Product and Sales around one positioning framework. You will help tell the story of the operating system for AI factories.
Key Responsibilities
Go-to-market launches: Own positioning, messaging, and launch execution end to end for new products and features, including products like vMetal that are early and still finding their sales motion.
Sales enablement that ships: Build the messaging, sales plays, and pitch decks the field actually uses, then coach sellers on how to run them. This is not a training-program role; you create the assets and the plays.
Content that proves the story: Produce and spec high-quality content across formats: blogs, guides, web copy, video, and social-ready assets, in partnership with design and brand.
Partner and ecosystem marketing: Work with AI Clouds and ecosystem partners (think NVIDIA-adjacent motions) to turn partnerships into pipeline-driving marketing.
Field insight loop: Get close to platform engineers, infrastructure owners, and the SE/TAM team to understand objections, friction, and competitive dynamics, and turn that into materials that move deals forward.
Messaging and positioning depth: You have built or refreshed a messaging framework for a technical product and can show the before and after.
GTM launch ownership: You have run launches yourself: the positioning, the bill of materials, the enablement, and the follow-through.
Sales enablement built by hand: You have created sales plays, pitch decks, and objection handling that sellers adopted, not just delivered training.
Cloud-native or infrastructure fluency: You have marketed products in the cloud infrastructure ecosystem (Kubernetes, monitoring, storage, networking, or a cloud provider). Deep Kubernetes expertise is a plus, not a requirement, but you must understand how the cloud-native stack fits together.
Build-phase experience: You have joined a company while the function was still being built and can describe what you stood up first and why.
A portfolio: High-quality samples of written work (long and short form), and ideally architecture diagrams, technical snippets, or video you drove. We ask for these in the application.
AI infrastructure exposure: Experience marketing to or for AI Clouds or AI infrastructure companies.
Partner marketing: Running co-marketing with major ecosystem partners.
Customer-facing depth: Time spent in front of platform engineering or infrastructure buyers (SE-adjacent, TAM-adjacent, or heavy field exposure).
We are a venture-backed tech startup and the company pioneering Kubernetes virtualization for the AI era. We raised +$30M from top-tier VCs such as Khosla Ventures (first investor in OpenAI, GitLab, Stripe, Doordash) and are in a hyper-growth phase looking for motivated people to complement our team. Our headquarters are in San Francisco (Salesforce Tower), but our team is distributed around the globe and we have a remote-first work culture.
We are the leading platform for operating GPU infrastructure, enabling AI Cloud providers to deliver a hyperscaler-like experience to their customers and AI factories that need to build that same experience for their internal teams. Our platform delivers the full operational stack operators need to run their GPU data centers — managed Kubernetes, fast isolated tenant provisioning, and automated node provisioning and lifecycle management — enabling them to accelerate time to value, reduce operational burden, and maximize the ROI of every GPU.
We're the company behind vCluster, an open-source technology for virtualizing Kubernetes (10k+ GitHub stars, 40M+ virtual clusters created since 2021). Open source is part of our DNA. At KubeCon North America 2025, we launched our Infrastructure Tenancy Platform for AI — a Kubernetes-native framework purpose-built for running AI, ML, and GPU-intensive workloads anywhere, with an NVIDIA-validated reference architecture for DGX systems.
