Director, AI Capacity Partnerships, Europe in London

Armada is the hyperscaler for the edge, delivering modular AI infrastructure from first deployment to AI factory with speed, scale, and sovereignty. Named one of Fast Company’s Most Innovative Companies and a CNBC Disruptor 50, Armada’s solutions are deployed in over 60 countries globally for organizations ranging from energy to defense.

This senior commercial role sits at the intersection of AI infrastructure, compute demand, and business development. You will build the demand side of Armada’s AI factory business by originating, qualifying, and converting off‑take demand for GPU capacity across our AI factory and Leviathan deployments.

What You’ll Do

• Originate and convert AI compute demand
• 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 off‑take, anchor tenant, reserved capacity, and strategic compute demand opportunities.
• Understand buyer requirements by GPU type, cluster size, geography, timing, power profile, tenancy model, and commercial structure—and turn that into actionable opportunities.
• Drive commercial outcomes for AI factory deployments
• Connect Armada’s AI factory and Leviathan deployments with credible compute users and potential off‑takers.
• 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 indirect 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 off‑take 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, and 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.

What We’re Looking For

We’re looking for someone who is commercially sharp, technically fluent, and deeply networked across the AI infrastructure ecosystem. A deep engineering background is not required, but sufficient technical fluency to earn trust with infrastructure teams, cloud buyers, and AI companies is essential.

You Likely Have:

• Existing, callable senior relationships across the AI compute ecosystem—neo‑clouds, GPU clouds, AI‑native companies, NVIDIA ecosystem partners, datacenter operators, infrastructure investors, or enterprise AI buyers.
• A track record of commercializing GPU capacity, cloud infrastructure, datacenters, managed compute, AI platforms, or high‑performance infrastructure.
• Experience structuring and closing complex infrastructure deals: off‑take 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.