Senior Manager, Sales Engineering – AI, GPU Cloud

🔥 14 hours ago

🏄 California – Remote

🏄 California – Remote

⏰ Full Time

🟠 Senior

💸 Sales 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

• 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 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 the team's technical quality bar • 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 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 reference architectures and joint pursuits • Influence product roadmap and packaging based on field insights

🎯 Requirements

• Hands-on experience running or standing up distributed training and/or production inference ML workloads • Practical fluency in data pipelines, distributed training, fine-tuning, and serving • Understanding of interconnect, memory bandwidth, I/O, and scheduling bottlenecks • Experience with PyTorch, 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 the NGC ecosystem • Understanding of the NVIDIA Cloud Partner motion and co-selling with NVIDIA • Track record supporting complex B2B deals with 6–18+ month cycles and large ACV/TCV • Experience 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 • Proven experience hiring, developing, and leading a sales engineering or solutions architecture team, or clearly demonstrated readiness to do so • Strongly preferred: experience selling GPU cloud, HPC, or specialized infrastructure • Preferred: Kubernetes, GPU operators/device plugins, Slurm, multi-cluster management, virtualized GPU/KubeVirt-style patterns, high-throughput parallel/object storage, data center economics, and sovereign/regulated/government AI buyers

🏖️ Benefits

• Professional development and training • Conference and working group attendance • Company outings, happy hours, hackathons, and tech talks • Competitive compensation package with a strong benefits plan • Remote work availability