Director, Presales Solution Architecture – NeoCloud

🔥 12 hours ago

🌐 Kazakhstan, United States – Remote

🇰🇿 Kazakhstan – Remote 🇺🇸 United States – Remote

⏰ Full Time

🔴 Lead

💻 Solutions Engineer

👻 Ghost score 19%

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

• Lead and build the sales engineering/solutions architecture team • Hire, coach, and retain sales engineers and solutions architects • Define the pre-sales operating model as the organization scales • Build discovery frameworks, reference architectures, TCO/benchmark models, POV playbooks, demo and benchmark environments, and RFP response libraries • Set and maintain a technical quality bar across the team • Run enablement on GPU architecture, networking, and orchestration • Partner with Account Executives as technical lead on strategic and enterprise opportunities from discovery through technical close • Run qualification using MEDDPICC or an equivalent methodology • Surface the economic buyer, decision criteria, and technical champion and build win plans • Architect solutions across compute, networking, storage, and orchestration • Produce sizing, capacity plans, and TCO comparisons against hyperscalers and self-build alternatives • Design and drive POCs/POVs, define success criteria, run benchmarks, and convert results into commercial momentum • Feed product and capacity requirements to product, platform, and supply/capacity planning teams • Work with NVIDIA field and partner ecosystem on joint pursuits and reference architectures • Influence product roadmap and packaging based on field feedback

🎯 Requirements

• Hands-on AI/ML infrastructure experience, including running or standing up distributed training and/or production inference workloads • Practical fluency in data pipelines, distributed training (multi-node/multi-GPU), fine-tuning, and serving • Understanding of interconnect, memory bandwidth, I/O, and scheduling bottlenecks • Experience with PyTorch and related tooling, including NCCL, CUDA-level concepts, containers, and schedulers • Deep knowledge of NVIDIA compute platforms, including Hopper and Blackwell generations, H100/H200, GB200 NVL72, B200-class systems, Grace-Hopper, DGX, HGX, and MGX • Knowledge of NVLink/NVSwitch, InfiniBand, Spectrum-X Ethernet, RDMA/RoCE, and DPUs • Knowledge of NVIDIA AI Enterprise, NIM, NeMo, Triton/TensorRT-LLM, Base Command, Run:ai/GPU orchestration, and NGC • Understanding of NVIDIA Cloud Partner motion and co-selling with NVIDIA • Track record supporting complex B2B deals with 6–18+ month sales cycles and large ACV/TCV • Experience with multi-year committed-capacity or reserved-capacity structures is ideal • Skilled at navigating ML/infra, platform engineering, procurement, finance, security, and executive stakeholders • Ability to build and defend TCO/ROI models against hyperscaler and on-premises alternatives • Ability to translate performance benchmarks into commercial value • Experience hiring, developing, and leading a sales engineering/solutions architecture team, or clear readiness to do so • Player-coach mindset • Strongly preferred: experience selling GPU cloud, HPC, or specialized infrastructure • Strongly preferred: Kubernetes, GPU operators/device plugins, Slurm, multi-cluster management, and storage-for-AI literacy • Familiarity with virtualized GPU/KubeVirt-style patterns is a plus • Experience with data center economics and constraints, including power, cooling, rack density, and capacity availability • Exposure to sovereign, regulated, or government AI buyers

🏖️ Benefits

• Professional development and training • Attend conferences and working groups • Company outings, happy hours, hackathons, and tech talks • Competitive compensation package with a strong benefits plan • Remote work arrangement (employees can work remotely)