Director, AI Capacity Partnerships, North America

About the role

This is a senior commercial role that sits at the intersection of AI infrastructure, compute demand, and business development.

Responsibilities

• Identify and engage organizations that need rapid access to GPU capacity - for training, inference, fine-tuning, enterprise AI, or sovereign AI workloads.
• Build a qualified pipeline of offtake, anchor tenant, reserved capacity, and strategic compute demand opportunities.
• Understand what buyers need by GPU type, cluster size, geography, timing, power profile, tenancy model, and commercial structure - and turn that into actionable opportunities.
• Connect Armada's AI factory and Leviathan deployments with credible compute users and potential offtakers.
• Shape demand strategy for new deployments - before, during, and after they go live.
• Translate market conversations into concrete next steps for commercial, infrastructure, finance, and legal teams.
• MATCH demand to deployable infrastructure.
• Map customer requirements to specific sites, GPU configurations, power availability, deployment timelines, cooling constraints, and commercial structures.
• Validate whether a demand opportunity is real, specific, and commercially viable.
• Bring customer insight into decisions on site selection, capacity planning, technical configuration, and go-to-market.
• OWN strategic accounts and relationships.
• Build and maintain direct relationships with senior decision-makers at key compute consumers.
• Track opportunities across timing, geography, technical requirements, commercial terms, and procurement processes.
• Keep high-value conversations moving - internally and externally.
• SHAPe commercial structures.
• Help design offtake agreements, capacity reservations, anchor tenancy models, revenue-share structures, and strategic partnership frameworks.
• Work across legal, finance, product, infrastructure, and executive stakeholders to take deals from interest to commitment.
• KNOW when an opportunity is real and when it isn't - and act accordingly.
• BE a market intelligence resource.
• Stay close to where demand is forming: which companies need capacity, which GPUs are in demand, what buyers are willing to commit to, how competitors are packaging AI infrastructure.
• FEED that intelligence into Armada's site selection, capacity planning, and deployment roadmap.
• HELP leadership understand the difference between real demand and speculative noise.

Requirements

We're looking for someone who is commercially sharp, technically fluent, and deeply networked across the AI infrastructure ecosystem.

Qualifications

• Existing, callable senior relationships across the AI compute ecosystem - neo-clouds, GPU clouds, AI-native companies, NVIDIA ecosystem partners, data center operators, infrastructure investors, or enterprise AI buyers.
• A track record of commercializing GPU capacity, cloud infrastructure, data centers, managed compute, AI platforms, or high-performance infrastructure.
• Experience structuring and closing complex infrastructure deals: offtake agreements, capacity reservations, anchor tenancy, revenue-share, or similar.
• The instincts to originate opportunities without a fully built playbook - and the discipline to follow through.
• Enough technical literacy to discuss GPUs, clusters, power density, liquid cooling, networking, latency, workload requirements, and deployment constraints with credibility.
• Strong pipeline discipline: clear account notes, sharp qualification, reliable follow-through.
• Executive presence and the ability to operate without a large corporate machine around you.

Skills

You understand:

• GPU supply and demand dynamics and how they shape commercial decisions.
• The NVIDIA ecosystem: programs, partners, buyers, and how they interact.
• How AI training and inference workloads translate into infrastructure requirements.
• Why power, cooling, geography, latency, interconnect, and deployment timing matter - and how buyers weigh them.
• How neo-clouds, AI-native companies, enterprises, and sovereign buyers think about compute capacity.
• The difference between speculative pipeline and real, committed demand.

Backgrounds We Value

• Neo-clouds or GPU cloud providers.
• NVIDIA ecosystem partners or programs.
• AI infrastructure startups.
• Data center platforms with AI or HPC exposure.
• Cloud infrastructure business development or strategic partnerships.
• AI platform companies selling into model builders or enterprise AI teams.
• HPC, GPU, or advanced compute infrastructure providers.
• Systems integrators or OEMs with real AI infrastructure customer access.
• Infrastructure investors or operators who have helped commercialize AI data center capacity.

Compensation & Benefits

• Compensation: $202,000 - $253,000 USD
• Benefits: Medical, dental, and vision (subsidized cost); Health savings accounts (HSA), flexible spending accounts (FSA), and dependent care FSAs (DCFSA); Retirement plan options, including 401(k) and Roth 401(k); Unlimited paid time off (PTO); 14 paid company holidays per year.