Technical Product Manager, Kubernetes Services (Remote, US)

About the role

Mirantis is looking for a Technical Product Manager to own the Kubernetes-as-a-Service offering for k0rdent AI, its control plane for GPU infrastructure and distributed AI workloads. You will define the strategy, roadmap and feature priorities for how Neocloud operators launch and run managed Kubernetes on their own GPU infrastructure. The role is remote and based in the US.

Key responsibilities

• Own the vision, roadmap and priorities for k0rdent AI Kubernetes services, defining how providers deliver, differentiate and operate managed Kubernetes for their own customers.
• Translate requirements from NeoClouds, GPU clouds, telcos, sovereign clouds and enterprise platform teams into clear product direction.
• Partner with engineering and architecture to define requirements, evaluate trade-offs and ship secure, scalable, reliable cluster lifecycle capabilities.
• Manage the Kubernetes backlog, refining roadmap priorities from production deployment and design partner feedback.
• Define positioning, packaging and competitive differentiation for the Kubernetes services.
• Create field-facing assets such as technical briefs, battlecards and reference architectures, and act as Kubernetes product lead for strategic accounts.
• Represent Mirantis at events, analyst briefings and customer advisory boards, and engage silicon, networking and ecosystem partners on reference architecture alignment.

Required profile

• 5+ years in product management, technical product management or a senior technical role owning a Kubernetes product, managed Kubernetes service or large-scale cluster fleet.
• Experience on the provider side of a service, at a cloud, hosting or platform organization treating users as paying customers.
• Experience configuring or deploying SLURM on Kubernetes (Slinky, Soperator or equivalent).

Required skills

• Strong technical fluency in Kubernetes operations and the AI stack.
• Familiarity with Cluster API, Kubernetes distributions and their lifecycle (k0s, kubeadm or equivalent), hosted or externally managed control planes, and add-on delivery via Helm and GitOps.
• Multi-tenancy and cluster hardening: RBAC, admission control, network policy, quotas, and certificate and kubeconfig lifecycle.
• Bare metal Kubernetes: node provisioning, CNI selection, load balancing and ingress, rolling upgrades, NVIDIA GPU Operator and device plugins.

What we offer

• Work on advanced AI infrastructure environments in production with NVIDIA GPU technologies and high-performance networking.
• Help define operational standards and reliability practices for next-generation AI infrastructure services.
• Influence the adoption of AI-powered operational capabilities through k0rdent AI.