AI Infrastructure Solution Architect - Kubernetes & NVIDIA

SUSE

Raleigh (NC)

On-site

USD 99,000 - 329,000

Full time

2 days ago
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Job summary

SUSE is seeking an AI Domain Solution Architect to join our North America team. This role requires deep expertise in AI infrastructure, accelerated computing, Kubernetes, and enterprise AI platforms, with the ability to translate that expertise into customer-ready solutions.

You will work inside the sales organization, partnering with Account Executives, Solution Architects, and customers to architect, validate, and demonstrate scalable AI workloads—from LLM inference to production

Qualifications

  • Experience translating deep technical expertise into customer solutions in presales and solution architecture.
  • Ability to simplify complex AI and infrastructure concepts for technical and executive audiences.

Responsibilities

  • Lead discovery sessions, architecture workshops, and infrastructure sizing for complex customer AI environments.
  • Develop PoCs, demonstrations, and technical proposals for RFI/RFP responses.
  • Explain governance and infrastructure requirements for agentic AI and multi-agent systems.
  • Collaborate with hardware vendors, SI partners, and cloud providers to optimize AI compute and storage.
  • Create reusable reference architectures and enable field teams across regions.
  • Capture customer feedback to inform product direction.

Skills

Presales Architecture
Technical Leadership
AI Infrastructure
NVIDIA Ecosystem
Kubernetes & Rancher
Linux Systems
SUSE Platform
High-Performance Networking
Security & Operations

Tools

NVIDIA AI Enterprise
Rancher Prime
SUSE AI Factory
Run:ai
NIM

Job description

SUSE is seeking an AI Domain Solution Architect to join our North America team. This role requires deep expertise in AI infrastructure, accelerated computing, Kubernetes, and enterprise AI platforms, with the ability to translate that expertise into customer-ready solutions.

You will work inside the sales organization, partnering with Account Executives, Solution Architects, and customers to architect, validate, and demonstrate scalable AI workloads—from LLM inference to production

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