解决方案架构主管 - AI 基础设施
Head of Solutions Architecture - AI Infrastructure
Mirantis，IREN公司，是一家以Kubernetes为核心的AI基础设施公司，帮助组织构建可扩展、安全且自主的基础设施，用于现代AI、机器学习和数据密集型应用。通过将开源创新与对Kubernetes编排的深入专业知识相结合，Mirantis使平台工程团队能够在任何环境中——本地、云上、边缘或自主数据中心——交付可组合、生产就绪的开发者平台。随着企业应对日益复杂的AI驱动工作负载，Mirantis提供所需的自动化、GPU编排和策略驱动的控制，以自信和敏捷的方式管理基础设施。致力于开放标准并避免供应商锁定，Mirantis确保客户对其基础设施战略拥有完全控制权。https://www.mirantis.com/
职位与使命简介
AI基础设施正在经历一代变革。分散的原始GPU硬件必须转化为多租户、生产就绪且自主的AI云——而不会让企业被单一超大规模供应商或硬件厂商锁定。这就是Mirantis的k0rdent AI所发挥的作用。
k0rdent AI作为声明式的“超级控制平面”，从Metal-to-Model™管理复杂的异构GPU基础设施。我们正在招聘一位解决方案架构负责人，负责技术胜出，从零开始建立预销售团队，并领导高价值、长周期计算交易的架构策略。
这不是一个演示角色。你将成为NeoClouds、AI原生初创公司、企业AI团队、研究实验室和自主买家的执行级技术合作伙伴。你将主导关于互连拓扑的高风险架构辩论，构建挑战超大规模经济的总拥有成本（TCO）模型，构建可复用的预销售机制，并直接从现场情报塑造我们的核心产品路线图。
你将负责
· 建设并扩展预销售引擎（40%）
· 招聘、指导并留住世界级的解决方案架构师和现场工程师；作为负责人，随着人员和交易量的增长，建立全球预销售运营模式。
- 构建可复用、可扩展的现场资产：发现框架、参考架构、TCO/基准模型、观点剧本和RFP响应库。
- 在整个组织中设定高标准的技术质量；进行培训，使每位SA都能可信地谈论GPU架构、高速光纤和容器化技术。
查看英文原文
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/
About the Role & Mission
AI infrastructure is undergoing a generational shift. Disaggregated, raw GPU hardware must be transformed into multi-tenant, production-ready, and sovereign AI clouds - without locking enterprises into a single hyperscaler or hardware vendor. That is where k0rdent AI by Mirantis comes in.
k0rdent AI serves as the declarative "super control plane" that manages complex, heterogeneous GPU infrastructure from Metal-to-Model™. We are hiring a Head of Solutions Architecture to own the technical win, build our pre-sales organization from the ground up, and lead the architecture strategy on high-value, long-cycle compute deals.
This is not a demo-jockey role. You will be an executive technical partner to NeoClouds, AI-native startups, enterprise AI teams, research labs, and sovereign buyers. You will lead high-stakes architecture debates on interconnect topologies, build TCO models that challenge hyperscaler economics, construct reusable pre-sales machinery, and shape our core product roadmap directly from field intelligence.
What You’ll Own
· Build & Scale the Pre-Sales Engine (40%)
· Hire, coach, and retain a world-class team of Solutions Architects and Field Engineers; establish the global pre-sales operating model as headcount and deal volume scale.
- Build reusable, scalable field assets: discovery frameworks, reference architectures, TCO/benchmark models, POV playbooks, and RFP response libraries.
- Set a high technical quality bar across the organization; run enablement so every SA can speak credibly to GPU architecture, high-speed fabrics, and container orchestration.
- Own the Technical Win in Strategic Deals (40%)
- Partner with Account Executives as the technical executive on strategic enterprise opportunities with long sales cycles (6–18+ months) and multi-million-dollar ACV/TCV.
- Execute structured qualification (MEDDPICC or equivalent) to map decision criteria, surface economic buyers, and build win plans around technical champions.
- Architect end-to-end solutions across compute, networking, storage, and orchestration; deliver sizing, capacity plans, and TCO comparisons vs. public clouds and self-built alternatives.
- Design and drive POVs/POCs: define strict success criteria upfront, run performance benchmarks, and convert results into commercial momentum.
- Serve as the Technical Voice of the Customer (20%)
- Feed structured product, capacity, and feature requirements directly back to product management, engineering, and supply planning teams.
- Partner closely with the NVIDIA field ecosystem (Cloud Partner program, reference architectures, joint pursuits) to win strategic accounts.
- Influence roadmap prioritization, packaging, and GTM strategy based on real-world field feedback.
By joining us, you will lead the technical field engine behind k0rdent AI, shaping how the world's most innovative companies build and operate GPU-powered infrastructure at scale.
What We’re Looking For
· Enterprise Deal Leadership: Proven track record leading technical sales in complex B2B environments, ideally with multi-year committed-capacity or reserved-capacity deal structures.
- Player-Coach Leadership: Track record of hiring, developing, and leading Solutions Architecture or Field Engineering teams—with the technical depth to lead the room on hard deals while scaling others to do the same.
- Hands-on AI/ML Infrastructure Experience: You have stood up or operated production ML workloads (distributed training and multi-node inference) and deeply understand performance bottlenecks across interconnect, memory bandwidth, I/O, and cluster scheduling.
- NVIDIA Stack & High-Speed Fabric Mastery: Fluency across Hopper and Blackwell architectures (H100/H200, GB200 NVL72, B200) and reference systems (DGX, HGX, MGX). Deep understanding of NVLink/NVSwitch domains, InfiniBand, Spectrum-X Ethernet, RDMA/RoCE, and DPUs.
Strongly Preferred:
· Pre-sales or infrastructure leadership experience at a NeoCloud, hyperscaler AI organization, or accelerated-hardware vendor.
- Hands-on experience with cloud-native orchestration for AI: Kubernetes (GPU operators, device plugins), KubeVirt, Metal3/Ironic bare-metal provisioning, and Slurm.
- Familiarity with high-throughput parallel/object storage systems for AI pipelines and data center physical constraints (power, cooling, rack density).
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