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Job description
Full-time
Company Description
About Mirantis
Mirantis is the Kubernetes-native AI infrastructure company, enabling organizations to build and operate scalable, secure, and sovereign infrastructure for modern AI, machine learning, and data-intensive applications. By combining open source innovation with deep expertise in Kubernetes orchestration, Mirantis empowers platform engineering teams to deliver composable, production-ready developer platforms across any environment - on-premises, in the cloud, at the edge, or in sovereign data centers. As enterprises navigate the growing complexity of AI-driven workloads, Mirantis delivers the automation, GPU orchestration, and policy-driven control needed to manage infrastructure with confidence and agility. Committed to open standards and freedom from lock-in, Mirantis ensures that customers retain full control of their infrastructure strategy.
Job Description
Mirantis is looking for a Technical Product Manager to own the Kubernetes-as-a-Service for k0rdent AI, our control plane for GPU infrastructure and distributed AI workloads. In this role, you will define the strategy, roadmap, and feature priorities that determine how Neocloud operators launch and run managed Kubernetes offerings on their own GPU infrastructure.
Managed Kubernetes sits at the intersection of cluster lifecycle automation and service provider operations, and the product must hold both worlds together. You will shape how k0rdent AI delivers validated cluster configurations and add-on compositions, hosted control planes at fleet scale, node pools bound to GPU machine types, tenant isolation, credential issuance, and upgrade cycles across hundreds of clusters. Operators assemble this today from bespoke automations and expertise that is difficult to source. Your job is to make it something a Neocloud configures rather than builds.
You will work directly with engineering to shape requirements, the rest of the Product Management team shaping k0rdent AI for providers, with marketing to sharpen positioning, and with field teams to convert technical depth into wins in competitive GPU cloud and NeoCloud deals.
Impact
Build the Kubernetes service layer for the AI cloud era, working directly with leading GPU cloud providers, NeoClouds, sovereign clouds, and AI-enabled telcos
Collaborate with a world-class, distributed team committed to openness and technical excellence
Shape the product narrative and influence go-to-market success
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, using feedback from production deployments and design partners to refine roadmap priorities and positioning
Define positioning, packaging, and competitive differentiation for k0rdent AI Kubernetes services
Create field-facing assets, including technical briefs, battlecards, and reference architectures; support strategic accounts as the Kubernetes product lead
Represent Mirantis at events, analyst briefings, and customer advisory boards; engage silicon, networking, and ecosystem partners on reference architecture alignment
Qualifications
Strong technical fluency in Kubernetes operations and the AI stack:
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
Hands-on familiarity with Cluster API, Kubernetes distributions and their lifecycle (k0s, kubeadm, or equivalent), hosted or externally managed control planes, and add-on delivery through Helm and GitOps
Fluency in multi-tenancy and cluster hardening: RBAC, admission control, network policy, quotas, and certificate and kubeconfig lifecycle
Hands-on experience running Kubernetes on bare metal, including node provisioning, CNI selection, load balancing and ingress, rolling upgrades across control planes and node pools, and the NVIDIA GPU Operator and device plugins
Experience on the provider side of a service, at a cloud or hosting company or a platform organization that treated its users as paying customers
Experience configuring or deploying SLURM on Kubernetes (Slinky, Soperator, or equivalent)
Additional Information
We offer:
Operate some of the most advanced AI infrastructure environments in production today.
Work with the latest NVIDIA GPU technologies, Kubernetes platforms, and high-performance networking environments.
Help define operational standards and reliability practices for next-generation AI infrastructure services.
Influence the adoption of AI-powered operational capabilities through k0rdent AI.
Work alongside highly skilled engineers solving complex infrastructure and platform challenges at scale.
Join a growing organisation investing heavily in AI infrastructure, platform services, and operational innovation.
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