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

Mirantis•San Jose, CA

18d

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, responsible for driving technical wins in complex, long-cycle deals for GPU clusters, bare metal, and managed AI infrastructure. The ideal candidate will have hands-on AI/ML infrastructure experience, deep knowledge of the NVIDIA platform, and a proven track record in enterprise sales engineering and team leadership. This position requires a player-coach mindset, capable of both architecting solutions and mentoring a team to achieve technical success in the competitive AI infrastructure market.

Requirements

Real, hands-on AI/ML infrastructure experience, including running distributed training and/or production inference workloads.
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 like PyTorch, NCCL, CUDA-level concepts, containers, and schedulers.
Deep knowledge of the NVIDIA platform and GPU products (Hopper and Blackwell generations, DGX, HGX, MGX).
Networking fluency: NVLink/NVSwitch, InfiniBand vs. Spectrum-X Ethernet, RDMA/RoCE, DPUs.
Familiarity with 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 long sales cycles (6–18+ months) and large ACV/TCV.
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 sales engineering/solutions architecture teams, and building processes from a greenfield start.
Player-coach mindset: credible in technical discussions 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, multi-cluster management.
Familiarity with virtualized GPU / KubeVirt-style patterns.
Storage-for-AI literacy, including high-throughput parallel/object storage.
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, and RFP response libraries.
Set and maintain a high technical quality bar across the team, ensuring credible communication on GPU architecture, networking, and orchestration.
Partner with Account Executives as the technical lead on strategic and enterprise opportunities from discovery through technical close.
Run qualification using methodologies like MEDDPICC to identify key stakeholders and build win plans.
Architect solutions encompassing compute, networking, storage, and orchestration, including sizing, capacity planning, and TCO comparisons.
Design and drive Proofs of Concept (POCs) and Proofs of Value (POVs), defining success criteria, running benchmarks, and converting results into commercial momentum.
Act 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.