Jobs · Engineering · Pennsylvania

AI Domain Solution Architect

SUSE · Philadelphia, PA · 3 wk ago
EngineeringFull-time
We need to output HTML fragment with sections: About the role? Actually the posting includes "About Us" and "Job Description". We need to use

for section headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections when posting has real specific content. We must not repeat job title as heading. Must not include Job ID etc. Remove boilerplate, navigation, legal, EEO, etc. Must preserve all substantive information. We need to parse the posting: It starts with "About Us SUSE is a global leader..." That's about the company, not necessarily "About the role". The instruction says use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we should map content to these headings if present. We have: - About Us: company description. Could map to "About the role"? Actually "About the role" is about the job, not company. But we have no explicit "About the role" section. However we have a paragraph after "AI Domain Solution Architect Job Description" that describes the role: "We are seeking an AI-focused Domain Solution Architect (DSA) to join our North America team. This role requires deep technical expertise..." That's about the role. So we can put that under

About the role

. - Responsibilities: there is a "Key Responsibilities" section with bullet points. So we can put

Responsibilities

with
  • items. - Skills & Experience: there is a "Skills & Experience" section with bullet points. That could map to Skills or Requirements/Qualifications. The instruction includes Skills, Requirements, Qualifications. We need to decide. The posting has "Skills & Experience". Likely map to Skills. Also there may be Requirements/Qualifications not separate. We could put Skills section. - Benefits: there is a "What We Offer" section describing benefits: "We empower you to be bold..." plus later "US benefits include comprehensive medical coverage..." Also there is "US Pay Transparency Disclaimer" with base pay range. So we have Pay and Benefits. - Pay: base pay range min & max: 99,000 329,000. Also mention commission plan, competitive benefits package. So we can include Pay section. - Schedule: not mentioned. So we should not include Schedule section. - Requirements/Qualifications: Not explicitly separate; maybe we can combine into Skills. But we could also create Requirements section from the "Skills & Experience" bullet points. However instruction says prefer few substantive sections over many thin ones. So we could have About the role, Responsibilities, Skills, Benefits, Pay. That's five sections. We must not include headings with filler like "commensurate with experience". Not needed. We must preserve all substantive information. Need to include details from About Us, role description, responsibilities, skills & experience, benefits, pay. We must remove boilerplate: cookie/navigation/legal/EEO/equal-opportunity/scam-warning, duplicated lines, application instructions. Also remove "Success in This Role" maybe? That's substantive? It describes success metrics. Could be part of About the role or Responsibilities? It's about success measurement. Could be included in About the role or maybe a separate section? Not listed as allowed headings. Could incorporate into About the role or Responsibilities. Probably include in About the role as extra paragraph. Also remove "This position is subject to a background check..." etc. That's legal boilerplate; should be removed. Remove "US Pay Transparency Disclaimer" maybe keep the pay range but discard the surrounding disclaimer? The instruction: preserve ALL substantive information; do not invent or summarize away detail. The pay range is substantive. The disclaimer about US only etc is also substantive? It's about pay transparency. Might be considered boilerplate but it's part of the pay info. However we can keep the pay range and mention that it's US base salary range. The disclaimer about commission plan and benefits is also substantive. We'll keep that. We must not include application instructions like "Click Apply..." etc. Remove that. We must not include "SUSE Values" etc? That's company culture; maybe considered substantive? It's not about the role directly. Might be considered boilerplate? It's about company values. Could be omitted as not directly about role. The instruction says remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. Values not listed; but could be considered generic marketing. Safer to omit? However we already have About Us description; we could keep that as About the role? Actually About Us is company overview. Might be considered substantive. We'll keep a brief About the role paragraph that includes the role description; we can also incorporate company description? The instruction says preserve ALL substantive information. The About Us is substantive about the company. Should we include it? There's no heading for About the company. Could we put it under About the role? Might be mixing. But we could create a section "About the role" that includes both role description and company overview? Might be okay. Better: Use About the role heading to include the paragraph describing the role and maybe also the company overview? The instruction says About the role heading for section headings (e.g. About the role, Responsibilities...). So we can put role description there. The About Us could be omitted as not directly about the role. But the instruction says preserve ALL substantive information; About Us is substantive about the company, not the role. However maybe it's considered part of job posting context; but they didn't give a heading for About the company. Could we treat it as part of About the role? Might be acceptable. Alternatively we could add a section "About the company" but not allowed headings list. So we should not create a heading not in list. So we must either omit About Us or incorporate into another allowed heading. Since we must preserve all substantive information, we need to include it somewhere. Perhaps we can put it in a

    without a heading? The instruction says use

    for section headings (e.g. About the role, Responsibilities...). It doesn't forbid having paragraphs without headings. So we can have a leading

    for About Us before any headings. That would preserve it. The instruction says Output ONLY the HTML fragment — no /, no markdown code fences. So we can start with a

    containing About Us text. Then headings. Thus structure:

    About Us SUSE is a global leader...

    Then

    About the role

    with paragraph describing role. Then

    Responsibilities

    with
      list. Then

      Skills

      with
        list (maybe combine Skills & Experience). Then

        Benefits

        with
          list (including US benefits, etc.) Then

          Pay

          with paragraph about base pay range, commission plan, etc. We must not include Schedule. We must ensure we don't repeat job title as heading. We must not include metadata like Job ID. We must remove duplicated lines. Now extract content. About Us paragraph: "SUSE is a global leader of enterprise open source software. By transforming community innovations into secure, sovereign and AI-ready solutions, SUSE empowers customers to escape vendor lock-in and regain control of their IT destiny. Through industry-leading Linux, Kubernetes, Edge and AI infrastructure solutions, SUSE delivers the flexibility to innovate everywhere—from the data center to multi-cloud and out to the edge. Only SUSE also manages many Linux and Kubernetes distributions. At SUSE, Choice Happens because we prioritize community, interoperability and relentless innovation. Discover how we power mission-critical resilience at www.suse.com." We'll keep that as a paragraph. About the role paragraph: "We 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." We could also include the "Success in This Role" paragraph: "Success 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." That's substantive; we can add to About the role or separate? Could add as another paragraph under About the role. Now Responsibilities: list items from "Key Responsibilities". Let's extract each bullet: - 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. We'll put each as
        • . Now Skills & Experience: list items: - 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 run

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