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vCluster Labs is seeking a Senior Product Manager to shape the product direction for their AI infrastructure platform. You'll work directly with the Head of Product and engineering leadership on strategic decisions that drive the company's growth trajectory.
Key Responsibilities:
- Define technical direction and business priorities for your product surface, translating them into executable engineering specifications
- Partner with the Head of Product and engineering leadership on architecture tradeoffs that determine product trajectory
- Conduct hands-on validation by running alpha and beta builds, catching integration issues before customers encounter them
- Engage directly with platform engineers at AI cloud operators, regulated enterprises, and large internal platform teams to identify zero-to-one opportunities
- Track the cloud-native ecosystem and emerging tenancy primitives to sharpen narrative for technical buyers
- Bridge engineering, sales, and marketing to ensure product delivery aligns with go-to-market strategy and customer support
About vCluster Labs:
vCluster Labs is a venture-backed startup (raised $28M+ from Khosla Ventures and others) providing the #1 platform for AI infrastructure. The company powers 100,000+ GPUs and 1M+ CPUs across 50+ AI clouds and Fortune 500 companies. The team is 40+ infrastructure engineers operating in a remote-first, distributed culture with headquarters in San Francisco. The company is behind vCluster, an open-source Kubernetes tenant isolation technology with 11,000+ GitHub stars and 40M+ tenant clusters created since 2021.
Requirements:
- 5+ years of product management experience in cloud infrastructure, platform services, or distributed systems
- Proven track record shipping products that other engineers depend on in production
- Working knowledge of Kubernetes, including clusters, workloads, and namespaces
- Comfortable engaging with platform engineers and architects in technical conversations
Bonus Experience:
- Kubernetes-as-a-Service (KaaS) offering experience at cloud providers, vendors, or large internal platform teams
- AI & MLOps infrastructure background (GPU scheduling, multi-tenant accelerator workloads, LLM deployment patterns)
- Internal Developer Platforms (IDP) product management experience
- Startup growth and adaptability to rapid change
