Senior Manager, Sales Engineering — AI / GPU Cloud (NeoCloud)

Mirantis•San Jose, CA

2d•Remote

About The Position

Mirantis, an IREN company, is seeking a Senior Manager, Sales Engineering for their NeoCloud division. This role is crucial for leading and building the sales engineering (SE) / Solutions Architect team, which is responsible for turning interested prospects into signed, multi-year committed-capacity contracts. The position requires a deep understanding of AI/ML infrastructure, particularly GPU orchestration, and experience in enterprise sales engineering with long sales cycles. The ideal candidate will have hands-on experience with AI/ML workloads, a strong grasp of the NVIDIA platform, and proven leadership skills in building and coaching technical teams. This role is pivotal in establishing Mirantis as a credible provider of accelerated compute solutions for Neoclouds, AI startups, enterprise AI teams, and research labs.

Requirements

Real, hands-on AI/ML infrastructure experience, including running or standing up ML workloads (distributed training and/or production inference).
Practical fluency in the training and inference lifecycle: data pipelines, distributed training (multi-node/multi-GPU), fine-tuning, and serving.
Comfort with customer frameworks and tooling, such as PyTorch and its ecosystem (NCCL, CUDA-level concepts, containers, schedulers).
Deep knowledge of the NVIDIA platform and GPU products, including Hopper and Blackwell generations (H100/H200, GB200 NVL72 / B200-class systems, Grace-Hopper superchips).
Networking fluency: NVLink/NVSwitch domains, InfiniBand vs. Spectrum-X Ethernet fabrics, RDMA/RoCE, DPUs.
Familiarity with NVIDIA software and platform layers: 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 cycles of 6–18+ months and large ACV/TCV, including multi-year committed-capacity or reserved-capacity structures.
Skilled at multi-stakeholder navigation (ML/infra leads, platform engineering, procurement, finance, security, executive sponsors).
Ability to build and defend TCO/ROI models and translate performance benchmarks into commercial value.
Proven team leadership experience, including hiring, developing, and leading a sales engineering/solutions architecture team, and building process/enablement from a greenfield start.
Player-coach mindset: capable of leading on the hardest deals while scaling others.

Nice To Haves

Experience selling GPU cloud, HPC, or specialized infrastructure, ideally at a NeoCloud/GPU-cloud provider, hyperscaler AI org, or accelerated-hardware vendor.
Hands-on experience with cloud-native and cluster orchestration for AI: Kubernetes (and GPU operators/device plugins), Slurm, and multi-cluster management.
Familiarity with virtualized GPU / KubeVirt-style patterns.
Storage-for-AI literacy: high-throughput parallel/object storage and its role in training pipelines.
Experience with data center economics and constraints: power, cooling, rack density.
Exposure to sovereign, regulated, or government AI buyers.

Responsibilities

Lead and build the SE / Solutions Architect team, including hiring, coaching, and retention.
Define the pre-sales operating model as the organization scales.
Build reusable pre-sales machinery such as discovery frameworks, reference architectures, TCO/benchmark models, POV playbooks, demo and benchmark environments, and RFP response libraries.
Set and maintain a high technical quality bar across the team, ensuring expertise in GPU architecture, networking, and orchestration.
Act as the technical lead on strategic and enterprise opportunities, partnering with Account Executives from discovery through technical close.
Utilize methodologies like MEDDPICC to run qualification, identify economic buyers, decision criteria, and technical champions.
Architect solutions encompassing compute, networking, storage, and orchestration, including sizing, capacity planning, and TCO comparisons.
Design and drive Proofs of Concept (POCs) / Proofs of Value (POVs), defining success criteria, running benchmarks, and converting results into commercial momentum.
Serve as the internal technical voice of the customer, feeding requirements back to product, platform, and supply/capacity planning teams.
Collaborate with the NVIDIA field and partner ecosystem to strengthen deals.
Influence product roadmap and packaging based on field insights.