VP of Presales Solutions Architecture - AI Infrastructure
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First recorded by Psst: 2 November 2026. Your first 3 jobs are free to apply to (the first right away, 2 more with your email). After that, the company and the apply link are for Psst members, from $4.99 for 7 days.
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The 20-second read
- Experience
- Senior
- Where you can live
- US only
- Skills and tools
- aws, kubernetes, machine learning, b2b, scheduling
- Job type
- Full-time
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Job details
- Where you can work
- United States
- Employment type
- Full-time
- Advertised pay
- Not stated by the employer
- Experience
- Senior
- Employer publication date
- 23 October 2026
- First recorded by Psst
- 2 November 2026
- Last checked at the source
- 10 November 2026
About the job
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 the company 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
- Pre-sales leadership experience at a NeoCloud, hyperscaler AI organization, or accelerated-hardware vendor
- 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
- 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).
We are a Leader for Container Management in G2 (#2 after AWS)!
The company, 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, the company 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, the company 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, the company ensures that customers retain full control of their infrastructure strategy. [link for members]
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