VP of Presales Solutions Architecture – AI Infrastructure

🕒 4 days ago

🇺🇸 United States – Remote

⏰ Full Time

🔴 Lead

💻 Solutions Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 22%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Mirantis

WebsiteLinkedInAll Job Openings

501 - 1000 employees

💼 Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

Mirantis is a company that specializes in container management and cloud infrastructure solutions. It offers a range of products, including Mirantis Kubernetes Engine (MKE), Mirantis OpenStack for Kubernetes (MOSK), and Mirantis Container Cloud (MCC), which provide enterprise-level Kubernetes and container management platforms. Mirantis also develops tools for secure software supply chains, such as the Mirantis Container Runtime (MCR) and Mirantis Secure Registry (MSR). As an advocate for open source technologies, Mirantis supports various projects and provides resources like Lens Desktop, a popular Kubernetes IDE, and technical support for enterprises adopting cloud-native technologies. Their solutions cater to sectors such as public services, financial services, and broader SaaS and technology services industries.

📋 Description

• Build and scale the global pre-sales organization • Hire, coach, and retain Solutions Architects and Field Engineers • Establish the global pre-sales operating model as headcount and deal volume scale • Build reusable discovery frameworks, reference architectures, TCO and benchmark models, POV playbooks, and RFP response libraries • Set technical quality standards and run enablement on GPU architecture, high-speed fabrics, and container orchestration • Partner with Account Executives as the technical executive on strategic enterprise opportunities • Lead technical sales for long-cycle opportunities of 6–18+ months and multi-million-dollar ACV/TCV • Execute structured qualification using MEDDPICC or equivalent • 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 and POCs, define success criteria, run performance benchmarks, and convert results into commercial momentum • Feed product, capacity, and feature requirements to product management, engineering, and supply planning teams • Partner with the NVIDIA field ecosystem on cloud partnerships, reference architectures, and joint pursuits • Influence roadmap prioritization, packaging, and go-to-market strategy based on field feedback

🎯 Requirements

• Pre-sales leadership experience at a NeoCloud, hyperscaler AI organization, or accelerated-hardware vendor • Proven track record leading technical sales in complex B2B environments • Experience with multi-year committed-capacity or reserved-capacity deal structures preferred • Track record of hiring, developing, and leading Solutions Architecture or Field Engineering teams • Technical depth to lead complex architecture and sales discussions • Hands-on experience standing up or operating production ML workloads, including distributed training and multi-node inference • 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 • Experience with NVIDIA reference systems including DGX, HGX, and MGX • Deep understanding of NVLink/NVSwitch, InfiniBand, Spectrum-X Ethernet, RDMA/RoCE, and DPUs • Strongly preferred: Kubernetes GPU operators and device plugins, KubeVirt, Metal3/Ironic bare-metal provisioning, and Slurm • Familiarity with high-throughput parallel/object storage systems for AI pipelines • Familiarity with data center physical constraints including power, cooling, and rack density

🏖️ Benefits

• Remote work • Opportunity to work with open source AI infrastructure, Kubernetes, GPU orchestration, and sovereign cloud technologies • Collaboration with NVIDIA field ecosystem and participation in joint pursuits