Senior Technical Product Marketing Manager, k0rdent AI (Remote)

About the role

Mirantis, a Kubernetes-native AI infrastructure company, is hiring a Senior Technical Product Marketing Manager for k0rdent AI, its AI infrastructure platform. The role is remote and focuses on the technical proof behind the product: white papers, demos, benchmarks and competitive analysis used by sales engineers, solution architects and customer infrastructure teams. It sits within the Product Marketing team, working closely with engineering, product management and solution architects.

Key responsibilities

• Write white papers, technical blogs, architecture decision guides and NVIDIA certification materials (NCP, NCX).
• Build and maintain the technical demo portfolio, including live demos, recorded walkthroughs and lab environments covering bare-metal provisioning, GPU cluster handoff and AI workload deployment.
• Lead technical competitive analysis, evaluating competing platforms and emerging neocloud control planes.
• Translate engineering and field data into defensible claims on cluster turn-up time, provisioning success rate, NCCL and fabric benchmarks, GPU utilization, failure-domain behavior and multi-tenant isolation.
• Run technical deep dives and architecture reviews with customers and prospects, and enable sales engineering and solution architects with POC criteria, test plans, discovery guides and sizing and TCO models.
• Support analyst and media briefings (Gartner, Forrester, S&P Global/451 Research, Omdia, technical press, podcasts) and present at conferences such as KubeCon, NVIDIA GTC and RAISE.
• Give product management structured roadmap input from POC patterns, recurring technical objections and competitive loss analysis.

Required profile

• 6+ years in 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: 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: inference serving (vLLM, TensorRT-LLM, NIM), training and scheduling (Slurm, Soperator), and MLOps tooling (Kubeflow, Ray).
• Experience presenting to and answering questions from infrastructure architects and technical buyers.
• Published technical writing portfolio (white papers or technical blogs) and willingness to travel for customer engagements and events.

Nice to have

• Background in GPU-as-a-service, neocloud, HPC or hyperscaler infrastructure, or direct NVIDIA ecosystem experience (DGX/HGX, GB200/GB300 NVL-class systems, BlueField DPUs, Spectrum-X or Quantum fabrics).
• Familiarity with Cluster API, k0s, k3s, Talos or similar cluster lifecycle tooling.
• Exposure to sovereign AI, regulated-industry or public-sector procurement.
• Record of accepted conference sessions or published technical writing.

What we offer

• Work on advanced AI infrastructure environments in production with the latest NVIDIA GPU technologies and Kubernetes platforms.
• Help define operational standards and reliability practices for next-generation AI infrastructure services.
• A growing organization investing heavily in AI infrastructure, platform services and operational innovation.