VP of Presales Solutions Architecture – AI Infrastructure

🕒 Outubro 23

🇺🇸 Estados Unidos – Remoto (EUA)

⏰ Tempo Integral

🔴 Especialista

💻 Engenheiro de Soluções

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👻 Score fantasma 23%

O que significa: a chance de ninguém estar realmente contratando para esta vaga.Como ler: 60% ou mais significa que achamos que é uma vaga fantasma. Pontuações mais baixas preocupam menos.Por que essa pontuação:

• Aberta há 18 dias.
• As vagas desta empresa costumam ser preenchidas em 38 dias.
• Sem salário divulgado.

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Mirantis

SiteLinkedInTodas as Vagas

501 - 1000 funcionários

💼 Consultoria

🏥 Saúde

📦 Logística

Consulting • Healthcare • Logistics

A Mirantis é uma empresa especializada em soluções de gerenciamento de contêineres e infraestrutura em nuvem. Ela oferece uma variedade de produtos, incluindo o Mirantis Kubernetes Engine (MKE), o Mirantis OpenStack para Kubernetes (MOSK) e o Mirantis Container Cloud (MCC), que fornecem plataformas de gerenciamento de Kubernetes e contêineres em nível empresarial. A Mirantis também desenvolve ferramentas para cadeias seguras de fornecimento de software, como o Mirantis Container Runtime (MCR) e o Mirantis Secure Registry (MSR). Como defensora das tecnologias de código aberto, a Mirantis apoia vários projetos e fornece recursos como o Lens Desktop, um popular IDE para Kubernetes, além de suporte técnico para empresas que adotam tecnologias nativas em nuvem. Suas soluções atendem a setores como serviços públicos, serviços financeiros e indústrias mais amplas de SaaS e serviços de tecnologia.

Descrição

• 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

🎯 Requisitos

• 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

🏖️ Benefícios

• 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

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