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Mirantis

Kubernetes management platform with services

Vice President of Presales Solutions Architecture - AI Infrastructure

Pre-Sales Solution EngineeringConfirmed live in the last 24 hours
Full-timeRemote in USANo salary listedRemote

About the Job

Requirements

  • Pre-sales leadership experience at a NeoCloud, hyperscaler AI organization, or accelerated-hardware vendor.
  • A proven track record leading technical sales in complex B2B environments, ideally with multi-year committed-capacity or reserved-capacity deal structures.
  • A track record of hiring, developing, and leading Solutions Architecture or Field Engineering teams, with the technical depth to lead complex deals while scaling others.
  • Experience standing up or operating production machine-learning workloads, including distributed training and multi-node inference, and deep understanding of performance bottlenecks across interconnect, memory bandwidth, I/O, and cluster scheduling.
  • Fluency across NVIDIA Hopper and Blackwell architectures, including H100/H200, GB200 NVL72, and B200, and reference systems including DGX, HGX, and MGX.
  • Deep understanding of NVLink/NVSwitch domains, InfiniBand, Spectrum-X Ethernet, RDMA/RoCE, and DPUs.

Responsibilities

  • Hire, coach, and retain a team of Solutions Architects and Field Engineers, and establish the global pre-sales operating model as headcount and deal volume scale.
  • Build reusable field assets, including discovery frameworks, reference architectures, TCO and benchmark models, POV playbooks, and RFP response libraries.
  • Set a high technical quality bar across the organization and run enablement so Solutions Architects can speak credibly about GPU architecture, high-speed fabrics, and container orchestration.
  • Partner with Account Executives as the technical executive on strategic enterprise opportunities with long sales cycles and multi-million-dollar ACV/TCV.
  • Execute structured qualification such as MEDDPICC or equivalent to map decision criteria, surface economic buyers, and build win plans around technical champions.
  • Architect end-to-end solutions across compute, networking, storage, and orchestration; deliver sizing, capacity plans, and TCO comparisons against public clouds and self-built alternatives.
  • Design and drive POVs/POCs by defining success criteria upfront, running performance benchmarks, and converting results into commercial momentum.
  • Feed structured product, capacity, and feature requirements to product management, engineering, and supply planning teams.
  • Partner with the NVIDIA field ecosystem, including the Cloud Partner program, reference architectures, and joint pursuits, to win strategic accounts.
  • Influence roadmap prioritization, packaging, and go-to-market strategy based on field feedback.

Desired Qualifications

  • Hands-on experience with cloud-native orchestration for AI, including Kubernetes GPU operators and device plugins, KubeVirt, Metal3/Ironic bare-metal provisioning, and Slurm.
  • Familiarity with high-throughput parallel and object storage systems for AI pipelines and data center physical constraints, including power, cooling, and rack density.

About the Company

Mirantis

Kubernetes management platform with services

Mirantis provides a Kubernetes management platform and related cloud services. It helps businesses run and scale containerized applications in the cloud by automating deployment, management, and scaling of Kubernetes clusters. The product is available as a free download, while the company earns revenue from professional services such as consulting, training, and support. This mix of software and services sets it apart from competitors that rely solely on software sales. Mirantis works with many clients across industries, focusing on helping organizations migrate to modern, scalable cloud solutions. The overall goal is to enable customers to operate their software more efficiently at large scale in the cloud.

Company size
501-1,000
Company stage
Acquired
Total funding
$255M
Headquarters
Mountain View, CA
Founded
1999

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