AI Domain Solution Architect
Job DescriptionWe are seeking an AI-focused Domain Solution Architect (DSA) to join our North America team. This role requires deep technical expertise in AI infrastructure, accelerated computing, Kubernetes, and enterprise AI platforms, combined with the ability to translate that expertise into solutions for complex customer environments.
As a Domain Solution Architect, you will be a technical specialist embedded within the sales organization, working alongside Account Executives, Solution Architects, partners, and customers to architect and validate enterprise AI solutions.
You will focus on helping customers move AI workloads from experimentation into secure, scalable, production-ready environments. The ideal candidate combines strong Kubernetes, Linux, and infrastructure architecture skills with hands-on knowledge of GPU-accelerated computing and the NVIDIA AI ecosystem.
Key Responsibilities- Drive Technical Architecture & Solution Design: Lead discovery sessions, technical evaluations, architecture workshops, and infrastructure sizing for complex customer AI environments-translating enterprise workloads such as LLM inference, fine-tuning, and RAG into scalable architectures built on SUSE AI Factory, Rancher Prime, and the NVIDIA accelerated computing stack.
- Deliver Technical Validation & Field Sales Execution: Partner with Account Executives and field Solution Architects throughout the sales cycle to lead technical qualification, build targeted PoCs, deliver hands-on demonstrations, and develop technical proposals and RFI/RFP responses.
- Guide Agentic AI Architecture: Help customers understand the infrastructure, integration, security, and governance requirements for agentic AI, multi-agent systems, and Model Context Protocol (MCP) integrations in enterprise production environments.
- Collaborate Across the AI Ecosystem: Jointly architect customer solutions with strategic ecosystem partners-including hardware vendors, systems integrators, and cloud providers-to optimize AI compute, high-speed networking, storage, and overall platform architecture.
- Build Field Capability & Repeatable Assets: Develop reusable reference architectures, solution blueprints, demonstrations, and technical enablement materials that scale AI expertise across regional and global field teams.
- Act as the Voice of the Customer: Capture technical feedback and emerging platform requirements from customer environments and communicate them to SUSE Product Management and Engineering to help inform product direction.
- Serve as an AI Infrastructure SME: Translate complex topics-including GPU architecture and partitioning, workload scheduling, multi-tenancy, high-performance networking, storage, and air-gapped operations-into clear technical and business value for audiences ranging from platform engineers to C-suite technology executives.
Skills & Experience- Presales Architecture Experience: Proven track record translating deep technical expertise into effective customer solutions, proposals, presentations, demonstrations, RFP responses, and hands-on workshops in a presales, solution architecture, or technical consulting role.
- Technical Communication & Leadership: Ability to simplify complex AI and infrastructure concepts for both technical and executive audiences, connecting technical architecture to business outcomes. Demonstrated ability to coordinate cross-functional teams, influence stakeholders in matrixed environments, and drive execution with a team-first mindset.
- AI Infrastructure & Accelerated Computing: Hands-on experience designing, operating, and sizing GPU-accelerated infrastructure for AI training, fine-tuning, and inference workloads. Practical understanding of GPU memory and compute characteristics, resource partitioning, workload scheduling, utilization, and multi-tenancy, together with familiarity with technologies such as vLLM, NIM, RAG, and vector databases.
- NVIDIA Ecosystem Proficiency: Working knowledge of the NVIDIA AI and accelerated computing ecosystem, including GPU architecture, NVIDIA AI Enterprise, CUDA, GPU and Network Operators, NCCL, GPUDirect, MIG, Run:ai, and high-performance interconnects.
- Container Management & Cloud-Native Platforms: Expert-level Kubernetes architecture and cluster administration experience, with RKE2, K3s, and Rancher Prime preferred. Deep proficiency with Helm, GitOps, CNI, container runtimes, observability, workload scheduling, and multi-cluster lifecycle operations.
- Linux Systems Expertise: Strong Linux systems knowledge, including networking, storage, containers, security, troubleshooting, and performance analysis in production environments.
- SUSE Platform Knowledge: Familiarity with, or the ability to rapidly acquire expertise in, SUSE AI Factory, SUSE Rancher Prime, SUSE Linux Enterprise Server (SLES), SUSE Security (NeuVector), and SUSE Observability.
- High-Performance Networking & Storage: Solid understanding of high-bandwidth, low-latency networking-including Ethernet, RoCEv2, RDMA, and InfiniBand-and distributed and object storage architectures supporting high-performance AI workloads.
- Enterprise Security & Operations: Experience designing secure production architectures, including container security, software supply-chain security, identity and access management, workload isolation, air-gapped/disconnected environments, and enterprise AI governance requirements.
Success in This RoleSuccess will be measured by your ability to bring deep AI infrastructure expertise into strategic customer opportunities, accelerate technical validation, enable field sales teams, develop repeatable AI solution patterns, and establish SUSE as a trusted platform for production enterprise AI.
For US Only - US Pay Transparency DisclaimerIf this role is filled in the United States of America, the starting base salary will be within the applicable pay range displayed below. In addition to base salary, this position may be eligible for a commission plan and a competitive benefits package. US benefits include comprehensive medical coverage, life and disability insurance, a 401(k) plan, an Employee Assistance Program, and generous paid time off and leave policies.
Final compensation will be determined based on factors such as experience, skills, geographic location, internal equity, and budget. This pay transparency information applies to US-based roles only.
Base Pay Range Min & Max99,000
329,000
JobSales
