Job description

Mirantis is seeking a Senior Technical Product Marketing Manager focused on k0rdent AI, our AI infrastructure platform. You will be responsible for the technical proof behind how we bring k0rdent AI to market: white papers, demos, benchmarks, and competitive analysis that sales engineers, solution architects, and customer infrastructure teams rely on. You will spend much of your time with customers, prospects, and the engineers and architects who build and deploy k0rdent AI, translating what you learn into technically defensible content and into feedback for product management. As part of the Product Marketing team, you will work hand in hand with engineering, product management, and solution architects to validate claims, build demos, and support customer technical deep dives and analyst briefings. The ideal candidate is a hands-on infrastructure practitioner who can write and present with authority. You will validate claims in the lab before they reach customers, understand where k0rdent AI wins and where it doesn't, and represent its capabilities accurately, including current limitations. Job Description: • Author white papers, technical blogs, architecture decision guides, and NVIDIA certification materials (NCP, NCX) for platform engineers and infrastructure architects. • Build and maintain the technical demo portfolio, including live demos, recorded walkthroughs, and supporting lab environments spanning bare-metal provisioning, GPU cluster handoff, and AI workload deployment. • Lead technical competitive analysis, including hands-on evaluation of competing platforms and emerging neocloud control planes. • Translate engineering and field data into defensible technical claims across cluster turn-up time, provisioning success rate at node scale, NCCL and fabric benchmark results, GPU utilization and allocation efficiency, failure-domain behavior, and multi-tenant isolation. • Engage directly with customers and prospects in technical deep dives and architecture reviews, alongside sales engineering and solution architects. • Enable sales engineering and solution architects with POC success criteria and test plans, discovery guides, and sizing and TCO models. • Support analyst and technical media briefings (Gartner, Forrester, S&P Global/451 Research, Omdia, technical press, podcasts), and present at conferences such as KubeCon, NVIDIA GTC, and RAISE. • Deliver structured roadmap input to product management based on POC patterns, recurring technical objections, and competitive loss analysis. Required qualifications: • 6+ years across technical product marketing, technical marketing engineering, solutions architecture, or infrastructure engineering, including externally facing technical content. Solution architects and TMEs moving into marketing are encouraged to apply. • Hands-on Kubernetes competence, including cluster operation, CRDs and controllers, and troubleshooting. • Depth in bare-metal and accelerated infrastructure across several of: server provisioning and lifecycle, InfiniBand and RoCE fabrics, GPU node provisioning and health, NVIDIA GPU Operator and MIG, DPUs, and data center power and cooling constraints. • Working knowledge of the AI infrastructure stack, including inference serving (e.g., vLLM, TensorRT-LLM, NIM), training and scheduling (e.g., Slurm, Soperator), and MLOps tooling (e.g., Kubeflow, Ray). • Experience presenting to and fielding questions from infrastructure architects and technical buyers. • Portfolio of published technical writing, including white papers, or technical blogs. • Willingness to travel for customer engagements and industry events. Soft skills and team fit: • Curious about how AI infrastructure works. • Strong cross-functional collaborator, comfortable with engineers, product managers, and executives. • Manages multiple projects and deadlines. • Passion for developer communities and the cloud-native ecosystem. • Bias toward shipping content and iterating quickly. Nice to have: • Background in GPU-as-a-service, neocloud, HPC, or hyperscaler infrastructure, as an operator or a vendor to them. • Direct NVIDIA ecosystem experience, including NCP and NCX certification programs, DGX/HGX and GB200/GB300 NVL-class systems, BlueField DPUs, and Spectrum-X or Quantum fabrics. • Familiarity with Cluster API, bare metal provisioning, k0s, k3s, Talos, or comparable cluster lifecycle tooling. • Exposure to sovereign AI, regulated-industry, or public-sector infrastructure procurement. • Record of accepted conference sessions or a body of published technical writing. 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. #Remote We are a Leader for Container Management in G2 (#2 after AWS)!

Requirements

Must-haves

Author white papers, technical blogs, architecture decision guides, and NVIDIA certification materials (NCP, NCX) for platform engineers and infrastructure architects.
Build and maintain the technical demo portfolio, including live demos, recorded walkthroughs, and supporting lab environments spanning bare-metal provisioning, GPU cluster handoff, and AI workload deployment.
Lead technical competitive analysis, including hands-on evaluation of competing platforms and emerging neocloud control planes.
Engage directly with customers and prospects in technical deep dives and architecture reviews, alongside sales engineering and solution architects.
Enable sales engineering and solution architects with POC success criteria and test plans, discovery guides, and sizing and TCO models.
Support analyst and technical media briefings (Gartner, Forrester, S&P Global/451 Research, Omdia, technical press, podcasts), and present at conferences such as KubeCon, NVIDIA GTC, and RAISE.
Deliver structured roadmap input to product management based on POC patterns, recurring technical objections, and competitive loss analysis.
Hands-on Kubernetes competence, including cluster operation, CRDs and controllers, and troubleshooting.
Working knowledge of the AI infrastructure stack, including inference serving (e.g., vLLM, TensorRT-LLM, NIM), training and scheduling (e.g., Slurm, Soperator), and MLOps tooling (e.g., Kubeflow, Ray).
Experience presenting to and fielding questions from infrastructure architects and technical buyers.
Portfolio of published technical writing, including white papers, or technical blogs.
Willingness to travel for customer engagements and industry events.
Curious about how AI infrastructure works.
Strong cross-functional collaborator, comfortable with engineers, product managers, and executives.
Manages multiple projects and deadlines.
Passion for developer communities and the cloud-native ecosystem.
Bias toward shipping content and iterating quickly.
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.

Nice-to-haves

Background in GPU-as-a-service, neocloud, HPC, or hyperscaler infrastructure, as an operator or a vendor to them.
Direct NVIDIA ecosystem experience, including NCP and NCX certification programs, DGX/HGX and GB200/GB300 NVL-class systems, BlueField DPUs, and Spectrum-X or Quantum fabrics.
Familiarity with Cluster API, bare metal provisioning, k0s, k3s, Talos, or comparable cluster lifecycle tooling.
Exposure to sovereign AI, regulated-industry, or public-sector infrastructure procurement.
Record of accepted conference sessions or a body of published technical writing.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aikubernetesllmapiaws

Platform: smartrecruiters
Effort: medium

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