Full-Time

Director AI Capacity Partnerships

Armada

Armada

501-1,000 employees

Real-time supply chain visibility platform

Compensation Overview

$202k - $253k/yr

+ Equity

Remote in USA

Remote

Remote within the United States.

Category
Business & Strategy (1)
Required Skills
Computer Networking

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Requirements
  • 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.
  • 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.
Responsibilities
  • 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 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.
  • Drive commercial outcomes for AI factory deployments: 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.
Desired Qualifications
  • 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.

Armada.ai provides a cloud-based Software-as-a-Service (SaaS) platform that improves visibility and collaboration across the supply chain. It serves logistics providers, manufacturers, and retailers, and connects them through real-time analytics and a shared workflow environment. The core product integrates with customers’ existing systems and offers dashboards, data-driven analytics, and social-network-like collaboration so stakeholders can share information, identify issues quickly, and coordinate responses. Unlike many traditional supply chain tools, Armada.ai focuses on real-time visibility and cross-partner collaboration within a single platform, leveraging integrations rather than replacing current systems. The company’s goal is to help customers run more efficient, cost-effective supply chains by enabling faster decisions and better coordination across all participants.

Company Size

501-1,000

Company Stage

Series B

Total Funding

$456M

Headquarters

San Francisco, California

Founded

2016

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Simplify Jobs

Simplify's Take

What believers are saying

  • Armada raised $230 million at a $2 billion valuation on May 19, 2026.
  • Johnson Controls, Mitsui, and Microsoft partnerships expand manufacturing, energy, and sovereign-cloud reach.
  • Customer demand drove 540 percent FY25-FY26 bookings growth and 2,000 percent Q1 FY27 year-on-year.

What critics are saying

  • NVIDIA, Microsoft, and Johnson Controls can commoditize Armada's control layer by 2027.
  • Galleon Forge One production starts summer 2026; factory delays will choke deployments.
  • A defense-heavy revenue mix exposes Armada to procurement freezes and one-customer concentration risk.

What makes Armada unique

  • Armada pairs Galleon modular data centers with Armada Edge Platform and Bridge orchestration.
  • Microsoft Azure Local integration targets sovereign private cloud in disconnected, contested environments.
  • NVIDIA AI Grid support validates Armada's multi-site orchestration for latency-sensitive AI workloads.

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Benefits

Company Equity

Growth & Insights and Company News

Headcount

6 month growth

3%

1 year growth

4%

2 year growth

4%
Insider Monkey
May 20th, 2026
Johnson Controls International (JCI) partners with Armada for development of Arizona factory.

Johnson Controls International (JCI) partners with Armada for development of Arizona factory. Published on May 20, 2026 at 2:37 pm by catherine talavera in news. Johnson Controls International plc (NYSE:JCI) is one of the 8 Best Climate Change Stocks to Buy According to Analysts. On May 19, modular data center builder Armada announced that it has entered an agreement with Johnson Controls for the development of the Galleon Forge One factory in Arizona. In a statement, Armada said Galleon Forge One will span up to 400,000 square feet and is projected to create 500 jobs, in addition to additional roles in the domestic supply chain. The company also unveiled a Global Framework Agreement for modular data center systems with Johnson Controls, adding that the latter is also making an investment in the company. Johnson Controls Chief Executive Officer Joakim Weidemanis said the company is working with Armada to rapidly deliver secure modular data centers at scale. He added: "Together, we have already deployed units across the United States and around the world, demonstrating the expertise and global reach required to support mission-critical environments. Johnson Controls' differentiated technology, U.S.-based manufacturing strength and Armada's edge computing expertise will deliver the thermal-critical environments that perform predictably, deploy quickly, and scale with confidence." Of the 25 analyst ratings compiled by CNN, 52% rated Johnson Controls Buy, while 36% assigned a Hold rating. The stock has an average price target of $155, a 14.46% upside from the current price of $135.42. Johnson Controls International plc (NYSE:JCI) is engaged in thermal management, mission-critical building systems, energy efficiency, and decarbonization. The company helps customers use energy more productively, reduce carbon emissions, and operate with precision. While we acknowledge the risk and potential of JCI as an investment, our conviction lies in the belief that some AI stocks hold greater promise for delivering higher returns and doing so within a shorter time frame. If you are looking for an AI stock that is more promising than JCI and that has 10,000% upside potential, check out our report about this cheapest AI stock.

Mitsui & Co.
May 20th, 2026
Mitsui invests in Armada to deploy AI infrastructure at industrial sites

Mitsui & Co has invested in Armada Systems Inc, a San Francisco-based provider of AI infrastructure solutions for industrial sites. The investment amount and valuation were not disclosed. Founded in 2022, Armada deploys modular data centres near industrial sites to enable real-time AI processing in harsh environments. Its integrated hardware and software platform supports operational automation, remote operations and predictive maintenance across sectors including oil and gas, manufacturing and mining. The company currently employs 400 people. Mitsui will leverage Armada's technology alongside its global network to develop edge data centre businesses and enhance AI capabilities across its metals and energy operations. The investment aligns with Mitsui's Medium-term Management Plan 2029, which prioritises data and AI integration across industrial sites.

Built In
May 20th, 2026
Edge computing company Armada raises $230M at $2B valuation.

Edge computing company Armada raises $230M at $2B valuation. The oversubscribed Series B will support growth as the company invests in modular data center production. Published on May. 20, 2026 Armada, an edge computing company providing modular AI infrastructure, secured $230 million in an oversubscribed Series B funding round co-led by Overmatch, BlackRock and 8090 Industries. The company, valued at $2 billion, also announced a framework agreement with Johnson Controls to establish production of Galleon Forge One, a modular data center, at a factory in Arizona. Galleon Forge One will span 400,000 square feet and is expected to create 500 jobs alongside various supply chain roles. Continuous production will commence in summer 2026, starting with Leviathan, Armada's megawatt-scale modular data centers for high-density AI training and inference workloads. In addition to the framework agreement, Armada secured an investment from Johnson Controls that furthers its ability to produce and deploy AI infrastructure where customers need it. "The AI race will not be won by one-off projects," Dan Wright, Armada's co-founder and CEO, said in a statement. "It will be won by the companies and countries that can manufacture, deploy and continuously improve AI infrastructure, with speed, scale and sovereignty. At Galleon Forge One, we will do what America does best: build the industrial base to win." Armada will invest its latest capital injection in supporting its growth initiatives and unlocking capacity for modular data centers.

FinSMEs
May 19th, 2026
Armada Raises $230M in Series B Funding

Armada, a San Francisco, CA-based infrastructure and artificial intelligence company developing an edge computing and satellite-enabled platform, raised $230M in Series B funding

Pipeshift
May 19th, 2026
Pipeshift partners with Armada to bring open-source inference to Bridge Marketplace.

Pipeshift partners with Armada to bring open-source inference to Bridge Marketplace. Armada Bridge customers can now access Pipeshift for production open-source LLM inference May 19, 2026 Partnership Pipeshift is excited to partner with Armada.ai as part of the launch of Bridge Marketplace, Armada's new ecosystem for validated AI infrastructure software. Through the marketplace, Armada Bridge customers can access Pipeshift for production open-source LLM inference. Pipeshift brings MAGIC, its model optimization framework for serving workloads across latency, throughput, and cost constraints. The partnership gives Bridge customers a direct way to run optimized model endpoints on secure compute infrastructure provided through Armada. Teams can use Pipeshift to turn open-source LLMs into inference services for internal applications, customer-facing products, and regulated AI workloads. Once the GPU infrastructure is available, the serving path still has to be built. Armada Bridge gives businesses a way to access secure compute infrastructure for AI workloads. That includes the operational layer around multi-tenant access, scheduling, orchestration, billing, infrastructure services, and platform services. Production AI still needs model endpoints that hold latency, throughput, and cost behavior under real demand. Pipeshift works on that inference path, optimizing runtime decisions such as: * how the model is served * how requests move through the runtime * how the endpoint balances latency, throughput, and cost MAGIC tunes the serving path around each workload. MAGIC is Pipeshift's model optimization framework for production inference. After a team selects a model and compute target, the serving setup still has to match the workload. Chat traffic, batch jobs, and long-context pipelines each need different runtime behavior. Different AI workloads put pressure on different parts of the serving path: * Chat and agent endpoints: prioritize first-token latency, streaming behavior, and queue control during traffic spikes * Coding workloads: need stable decode performance across longer responses and concurrent users * Long-context and RAG workloads: put heavier pressure on prefill, memory movement, and cache reuse * Batch inference jobs: push for higher GPU utilization while keeping them away from latency-sensitive endpoints * Structured-output endpoints: need reliable formatting and tool-call behavior without adding heavy serving overhead The diagram below shows the flow from Armada Bridge compute infrastructure to a workload-specific inference endpoint. MAGIC gives each workload a serving path matched to its runtime pressure. A latency-sensitive endpoint, a long-context pipeline, and a batch job each need different runtime assumptions. Bridge customers can use Pipeshift to run open-source models as purpose-built inference endpoints on compute infrastructure provided through Armada. AI teams should be able to request model endpoints directly. For Bridge customers, Pipeshift makes secure compute infrastructure easier to use for production model serving. AI demand rarely arrives as one clean workload. A coding assistant, internal RAG system, support agent, and batch summarization job can run inside the same business with different serving requirements. Those requests may involve Qwen, Llama, DeepSeek, Mistral, Gemma, or another open-source model the team wants to run. Infrastructure teams need a repeatable serving layer for new models, workloads, and application requirements. And, the operators need a repeatable serving layer for new models, workloads, and tenant requirements. Pipeshift helps standardize that layer across open-source inference deployments. A new endpoint can start from a known serving pattern, then get tuned for the model, workload, and capacity target. Pipeshift is excited to support Armada customers building production AI infrastructure. Pipeshift is glad to support the launch of Armada Bridge Marketplace. Armada Bridge customers can find Pipeshift in the marketplace to explore production open-source LLM inference on secure compute infrastructure provided through Armada. Teams that want to discuss a specific model, workload, or deployment target can also reach out to Pipeshift directly.