Qualifications:- 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.
Preferred Qualifications:- NVIDIA-certified or equivalent AI/ML platform certifications.
- Cloud architecture certifications (AWS SA Pro, Azure Solutions Architect, GCP PCA).
- Prior experience working at a top-tier solutions provider, related OEM, or cloud provider.
- Experience designing AI Factory / GPU cluster architectures at enterprise scale.
Regional travel up to 40%
Certain states and localities require employers to post a reasonable estimate of salary range. A reasonable estimate of the current base pay range for this position is $185,000.00 to $235,000.00 annually. Actual salary will be based on a variety of factors, including shift, location, experience, skill set, performance, licensure and certification, and business needs. The range for this position in other geographic locations may differ. Certain positions may also be eligible for variable incentive compensation, such as bonuses or commissions, that is not included in the base pay.
Want to learn more about Enterprise AI Strategy & GTM Execution? Check us out on our platform:
https://www.wwt.com/all-categories/artificial-intelligence
The well-being of WWT employees is essential. So, when it comes to our benefits package, WWT has one of the best. We offer the following benefits to all full-time employees:
- Health and Wellbeing: Health, Dental, and Vision Care, Onsite Health Centers, Employee Assistance Program, Wellness program
- Financial Benefits: Competitive pay, Profit Sharing, 401k Plan with Company Matching, Life and Disability Insurance, Tuition Reimbursement
- Paid Time Off: PTO & Holidays, Parental Leave, Sick Leave, Military Leave, Bereavement
- Additional Perks: Nursing Mothers Benefits, Voluntary Legal, Pet Insurance, Employee Discount Program
We strive to create an environment where all employees are empowered to succeed based on their skills, performance, and dedication. Our goal is to cultivate a culture of belonging that encourages innovation, collaboration, and respect for all team members, ensuring that WWT remains a great place to work for All!
#LI-MG2What is the Enterprise AI Strategy & GTM Execution team?WWT's Enterprise AI Strategy & GTM Execution team is at the center of WWT's AI transformation, responsible for leading the company's go-to-market motion across the full AI solution stack - from infrastructure and platforms to consulting, advisory, and managed services. The team will serve as the primary bridge between WWT's enterprise AI capabilities and the customers who need them most. This is a rare opportunity to be a part of a purpose-built AI sales organization at one of the world's leading technology solutions providers, with the backing of WWT's Advanced Technology Center, world-class OEM partnerships, and a culture built on collaboration, accountability, and innovation.
What will you be doing?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.
Success requires deep technical currency across the AI ecosystem, strong communication skills that translate complexity into business-relevant narratives, and an ego-free collaborative approach to co-selling with the AI Solutions Executive, AI Services Consultant, field account teams, NVIDIA-embedded resources, and WWT delivery engineering.
Responsibilities:Technical Pre-Sales & Solution Design- Serve as the technical counterpart to the AI Solutions Executive in all customer-facing engagements.
- Translate customer business problems into AI solution architectures spanning GPU/compute, data platforms, AI/ML frameworks, networking, storage, and application layers.
- Lead technical discovery sessions with customer engineering and data science teams, and produce reference architectures, BoMs, sizing models, and POC plans that drive decision-making and inform commercial proposals.
ATC & Proof-of-Concept Coordination- Partner with WWT's Advanced Technology Center to design and execute lab environments, benchmarks, and customer immersion sessions that validate proposed AI architectures.
- Lead technical execution of ATC engagements end-to-end and position lab-led validation as a competitive differentiator that de-risks customer commitment.
NVIDIA & Partner Technical Alignment- Maintain deep technical currency across the NVIDIA ecosystem (DGX/HGX, CUDA, AI Enterprise, NeMo, Omniverse) and work directly with NVIDIA resources on GPU design validation, NVAIE integration, and configuration optimization.
- Collaborate with hyperscaler 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- Ensure proposed architectures are technically feasible, accurately scoped, and clearly documented for a clean transition to services and engineering teams.
- Participate in SOW validation alongside the AI Services Consultant and provide ongoing technical consultation to delivery teams during complex implementations as needed.
POD & Cross-Functional Collaboration- Function as an integrated member of the three-person regional POD (AI Solutions Executive, AI Solutions Architect, AI Services Consultant), contributing to joint pipeline reviews, account planning, and weekly cadence.
- Embed with field sales teams to surface AI opportunities and build their confidence through technical training, architecture overviews, and lunch-and-learn sessions.
- Contribute competitive intelligence and customer adoption insights back to the broader AI practice.
