Director, Presales Solution Architecture

🔥 3 minutes ago

🌐 Kazakhstan, United States – Remote

🇰🇿 Kazakhstan – Remote 🇺🇸 United States – Remote

⏰ Full Time

🔴 Lead

💻 Solutions Engineer

👻 Ghost score 20%

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.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

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 and solutions architecture team • Hire, coach, and retain sales engineers and solutions architects • Define the pre-sales operating model and build discovery frameworks, reference architectures, TCO/benchmark models, POV playbooks, demo and benchmark environments, and RFP response libraries • Set technical quality standards and 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 • Architect solutions across compute, networking, storage, and orchestration • Produce sizing, capacity plans, and TCO comparisons • Design and drive proofs of concept and proofs of value, including benchmarks and success criteria • Feed product and capacity requirements to product, platform, and supply/capacity planning teams • Work with NVIDIA field and partner ecosystem on reference architectures and joint pursuits • Influence product roadmap and packaging based on field insights

🎯 Requirements

• Hands-on AI/ML infrastructure experience running or standing up distributed training and/or production inference workloads • Practical fluency in data pipelines, distributed training, fine-tuning, serving, interconnect, memory bandwidth, I/O, and scheduling • Experience with PyTorch, NCCL, CUDA-level concepts, containers, and schedulers • Deep knowledge of NVIDIA Hopper and Blackwell platforms, including 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 • Track record supporting complex B2B deals with 6–18+ month cycles and large ACV/TCV • Ability to navigate ML/infra, platform engineering, procurement, finance, security, and executive stakeholders • Ability to build and defend TCO/ROI models against hyperscaler and on-premises alternatives • Proven sales engineering or solutions architecture team leadership, including hiring, development, process, and enablement • Preferred: experience selling GPU cloud, HPC, or specialized infrastructure • Preferred: Kubernetes, GPU operators/device plugins, Slurm, multi-cluster management, and virtualized GPU/KubeVirt patterns • Preferred: storage-for-AI literacy, data center economics, and 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