- Minimum 10 years in technical pre-sales, solutions architecture, or advanced engineering roles at a solutions provider, OEM, cloud provider, or consulting firm.
- Hands-on experience designing AI/ML infrastructure and platforms. Must be able to whiteboard an end-to-end AI architecture from GPU cluster design through networking, storage, software staock, MLOps pipeline, and inference deployment.
- Working knowledge of NVIDIA DGX/HGX systems, CUDA, AI Enterprise software suite, and partner integration patterns.
- Experience with AI workloads across on-premises, cloud (AWS, Azure, GCP), and hybrid environments. Understanding of NCP models, GPU-as-a-service, and sovereign AI infrastructure.
- Exceptional ability to translate technical complexity into business-relevant narratives. Strong presentation and whiteboarding skills.
- Comfortable operating in a revenue-generating, pre-sales context. Understands that the purpose of technical engagement is to advance deals.
- Experience collaborating in co-selling models with sales specialists, field account teams, and partner SE resources.
- Bachelor’s degree in computer science, engineering, or related field required.
- NVIDIA-certified or equivalent AI/ML platform certifications.
- Cloud architecture certifications (AWS SA Pro, Azure Solutions Architect, GCP PCA).
- Prior experience at a top-tier solutions provider, related OEM, or cloud provider.
- Experience designing AI Factory / GPU cluster architectures at enterprise scale.
- Familiarity with WWT’s Advanced Technology Center model and lab-led selling methodology.
- Masters or advanced degree in technology, analytics, or business preferred.
#LI-RB1
Preferred QualificationsWhy WWT?
World Wide Technology (WWT) strives to make a new world happen. WWT's work benefits clients and partners as much as it does its people and community across the globe.
Founded in 1990, WWT brings together strategy, deep technical expertise and world-class partnerships to help public and private sector organizations design, build and scale intelligent AI, digital, cybersecurity, cloud and infrastructure solutions. Through its Advanced Technology Center (ATC) - a collaborative ecosystem featuring state-of-the-art hardware and software - WWT enables clients and partners to conceptualize, test and validate innovative technology and then deploy solutions at scale using its global integration and distribution capabilities.
With more than 14,000 team members and over 60 locations globally, WWT's culture—grounded in core values and leadership philosophies—has been recognized by Fortune® and Great Place to Work for its commitment to innovation, trust and creating a great place to work for all.
WWT provides products and services to large enterprise, global service provider and public sector clients in up to 130 countries across six continents. Softchoice, a World Wide Technology company, supports commercial and SMB markets in the U.S. and Canada.
Position Summary- The AI Solutions Architect is the technical pre-sales partner within each regional AI POD. This role brings hands-on architectural expertise into customer engagements during the pre-sales phase, translating customer business requirements into concrete AI solution designs, reference architectures, and technical proposals that give WWT credibility and differentiation in competitive pursuits.
This is not a delivery or post-sales engineering role. The AI Solutions Architect operates in a revenue-generating context, working alongside the AI Solutions Executive to win deals by providing the technical depth that enterprise customers require before committing to AI investments. The role demands the ability to whiteboard an end-to-end AI architecture in a customer meeting, coordinate proof-of-concept engagements through WWT’s Advanced Technology Center (ATC), and ensure that what is sold can be built, scoped accurately, and transitioned cleanly to delivery teams.
Key Responsibilities-
Technical Pre-Sales & Solution Design
- Serve as the technical counterpart to the AI Solutions Executive in all customer-facing engagements, providing architectural depth, solution credibility, and technical validation.
- Translate customer business problems into AI solution architectures spanning GPU/compute infrastructure, data platforms, AI/ML frameworks, networking for AI, storage, and application layers.
- Design and present technical proposals, reference architectures, and proof-of-concept plans that accelerate customer decision-making and de-risk complex AI deployments.
- Conduct technical discovery sessions with customer platform engineering, data science, and infrastructure teams to assess environment readiness (including space, power, cooling), workload requirements, and integration complexity.
NVIDIA & Partner Technical Alignment
- Work directly with NVIDIA resources aligned with target accounts on GPU/compute-specific design validation, NVAIE software stack integration, and DGX/HGX configuration optimization.
- Maintain deep technical currency across the NVIDIA ecosystem: DGX/HGX systems, CUDA, AI Enterprise, NeMo, Omniverse, etc. and partner integration patterns.
- Collaborate with cloud provider and infrastructure partner teams (AWS, Azure, GCP, Dell, HPE, Cisco, NetApp, Pure Storage, Vast Data, +) on hybrid and multi-cloud AI architecture design.
Pre-Sales to Delivery Handoff
- Bridge the gap between pre-sales and delivery: ensure that solution architectures are technically feasible, scoped accurately, and documented for clean transition to services and engineering teams.
- Participate in scope reviews and SOW validation alongside the AI Services Consultant to ensure alignment between what is proposed and what will be delivered.
- Provide post-handoff technical consultation as needed to support delivery teams during implementation of complex architectures.
POD & Cross-Functional Collaboration
- Operate as an integrated member of the three-person regional POD (AI Solutions Executive, AI Solutions Architect, AI Services Consultant), participating in weekly POD cadence, joint pipeline reviews, and account planning.
- Operate as a trusted AI subject matter resource to field sales teams, embedding into account planning and strategy sessions to surface AI opportunities.
- Build strong working relationships with field sales teams across the assigned region, earning inclusion in customer conversations and account reviews through consistent value delivery.
