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

Real, hands-on AI/ML infrastructure experience

You have actually run or stood up ML workloads — distributed training and/or production inference — not just talked about them.

Practical fluency in the training and inference lifecycle: data pipelines, distributed training (multi-node/multi-GPU), fine-tuning, and serving; you understand where bottlenecks actually live (interconnect, memory bandwidth, I/O, scheduling).

Comfortable in the frameworks and tooling customers use — PyTorch and the surrounding ecosystem (e.g., NCCL, CUDA-level concepts, containers, schedulers).

Deep knowledge of the NVIDIA platform and GPU products

Current on the NVIDIA compute stack across the Hopper and Blackwell generations (e.g., H100/H200, GB200 NVL72 / B200-class systems, Grace-Hopper superchips) and the reference-system families (DGX, HGX, MGX); aware of what's coming next-generation.

Networking fluency: NVLink/NVSwitch domains, InfiniBand (Quantum) vs.

Spectrum-X Ethernet fabrics, RDMA/RoCE, DPUs — and why fabric choice makes or breaks large training clusters.

Software and platform layer: NVIDIA AI Enterprise, NIM, NeMo, Triton / TensorRT-LLM, Base Command, Run:ai / GPU orchestration, and the NGC ecosystem.

Understands the NVIDIA Cloud Partner motion and how to co-sell with NVIDIA.

Enterprise sales engineering on long, high-value cycles

Track record supporting complex B2B deals with cycles of 6–18+ months and large ACV/TCV, ideally including multi-year committed-capacity or reserved-capacity structures.

Skilled at multi-stakeholder navigation — ML/infra leads, platform engineering, procurement, finance, security, and executive sponsors.

Can build and defend a TCO/ROI model against hyperscaler and on-prem alternatives, and translate performance benchmarks into commercial value.

Proven team leadership

Has hired, developed, and led a sales engineering / solutions architecture team (or clearly demonstrated the readiness to), including building process and enablement from a light or greenfield starting point.

Player-coach mindset: still credible in the room on the hardest deals, while scaling others to do the same.

Strongly preferred

Experience selling GPU cloud, HPC, or specialized infrastructure — ideally at a NeoCloud / GPU-cloud provider, hyperscaler AI org, or accelerated-hardware vendor.

Hands-on with cloud-native and cluster orchestration for AI: Kubernetes (and GPU operators / device plugins), Slurm, and multi-cluster management approaches; familiarity with virtualized GPU / KubeVirt-style patterns is a plus.

Storage-for-AI literacy — high-throughput parallel/object storage and its role in training pipelines.

with data center economics and constraints: power, cooling, rack density, and how capacity availability shapes deals.

Exposure to sovereign, regulated, or government AI buyers.

What does Mirantis offer you?

• Work with an established Silicon Valley leader in the cloud infrastructure industry;
• Work with exceptionally passionate, talented and engaging colleagues, helping Fortune 500 and Global 2000 customers implement next-generation cloud technologies;
• Be a part of cutting-edge, open-source innovation;
• Thrive in the high-energy environment of a young company where openness, collaboration, risk-taking, and continuous growth are valued;
• Professional development and training;
• Attend conferences and working groups;
• Company outings, happy hours, hackathons, and tech talks;
• Receive a competitive compensation package with a strong benefits plan.

We are a Leader for Container Management in G2 (#2 after AWS)!

Mirantis, an IREN company, is the Kubernetes-native AI infrastructure company, enabling organizations to build and operate scalable, secure, and sovereign infrastructure for modern AI, machine learning, and data-intensive applications.

By combining open source innovation with deep expertise in Kubernetes orchestration, Mirantis empowers platform engineering teams to deliver composable, production-ready developer platforms across any environment—on-premises, in the cloud, at the edge, or in sovereign data centers.

As enterprises navigate the growing complexity of AI-driven workloads, Mirantis delivers the automation, GPU orchestration, and policy-driven control needed to manage infrastructure with confidence and agility.

Committed to open standards and freedom from lock-in, Mirantis ensures that customers retain full control of their infrastructure strategy. https://www.mirantis.com/