AI Factory Customer Engineer
armada • Netherlands (Remote)
No Relocation
Posted: March 25, 2026
Job Description
About the Role
The AI Factory Customer Engineer plays a pivotal role in bridging the gap between customers and Armada’s Product and Engineering teams. This role requires deep technical credibility, hands‑on infrastructure experience, and strong interpersonal skills to translate complex AI infrastructure and data center architectures into clear, practical customer solutions.
This role goes beyond traditional pre‑sales. The Customer Engineer acts as the primary technical interface between customers and Armada Engineering, ensuring customer requirements, constraints, and feedback are accurately represented in solution design and incorporated into the evolution of the AI Factory platform.
Armada’s AI Factory serves a broad and growing customer base across enterprise, industrial, and infrastructure‑heavy verticals. Strategic customer segments include AI data center co‑location providers, Neocloud operators, renewable energy operators, telecoms, MSPs, and land‑and‑power asset owners. These customers rely on Armada’s modular, liquid‑cooled AI Factory for rapid, scalable deployment of high‑density AI compute.
The ideal candidate brings an engineering‑first mindset, strong expertise in modular and liquid‑cooled data centers, GPU‑based systems, and the energy, curiosity, and positivity required to thrive in fast‑moving and ambiguous environments. This role is instrumental in driving adoption, trust, and long‑term customer success.
Location: Remote
Location: Remote
Key Responsibilities
Core Technical Customer Engagement
- Serve as the primary technical partner between customers and Armada’s Product and Engineering teams, translating real‑world requirements into actionable designs.
- Provide hands‑on technical guidance on AI Factory solutions, including modular and liquid‑cooled data centers and NVIDIA‑based GPU systems.
- Advise customers on workload suitability, rack‑level design, system architecture, and deployment tradeoffs.
- Lead technical demos, proofs‑of‑concept, and working sessions tailored to customer environments and constraints.
- Build trusted‑advisor relationships with engineering, infrastructure, IT, OT, and security stakeholders.
- Enable Sales and field teams by distilling complex infrastructure topics into clear, outcome‑driven narratives.
- Take end‑to‑end ownership of technical engagements, bringing curiosity, urgency, and a problem‑solving mindset.
Required Qualifications & Technical Expertise
- Bachelor’s degree in Engineering, Computer Science, or related field (or equivalent hands‑on experience); advanced degrees a plus.
- 5+ years of experience in data center engineering, infrastructure engineering, pre‑sales/sales engineering, or solution architecture.
- Strong foundation in compute, networking, and storage, including GPU‑based AI systems (e.g., NVIDIA DGX, HGX, MGX).
- Hands‑on experience with data center infrastructure, including MEP systems, cooling architectures, and rack‑level design.
- Deep familiarity with modular and/or liquid‑cooled data center architectures, power density, and thermal management.
- Ability to translate AI workload requirements into scalable, production‑ready infrastructure designs.
- Working knowledge of cloud platforms, containerization, virtualization, and modern enterprise infrastructure.
- Comfort operating in complex, live customer environments, with strong troubleshooting skills.
- Ability to build credibility across IT and OT stakeholders, particularly in industrial or energy‑adjacent contexts.
- Excellent communication skills, capable of engaging both deeply technical teams and executive audiences.
- Willingness to travel as required.
Nice to Have:
- Exposure to energy, utilities, telecom, oil & gas, or industrial infrastructure environments.
- Understanding of power generation, distribution, or energy‑driven deployments.
- Familiarity with AI data center co‑location or Neocloud models.
- Experience with regulated or mission‑critical systems and structured sales methodologies (e.g., MEDDPICC, Challenger).
Additional Content
About the Role
The AI Factory Customer Engineer plays a pivotal role in bridging the gap between customers and Armada’s Product and Engineering teams. This role requires deep technical credibility, hands‑on infrastructure experience, and strong interpersonal skills to translate complex AI infrastructure and data center architectures into clear, practical customer solutions.
This role goes beyond traditional pre‑sales. The Customer Engineer acts as the primary technical interface between customers and Armada Engineering, ensuring customer requirements, constraints, and feedback are accurately represented in solution design and incorporated into the evolution of the AI Factory platform.
Armada’s AI Factory serves a broad and growing customer base across enterprise, industrial, and infrastructure‑heavy verticals. Strategic customer segments include AI data center co‑location providers, Neocloud operators, renewable energy operators, telecoms, MSPs, and land‑and‑power asset owners. These customers rely on Armada’s modular, liquid‑cooled AI Factory for rapid, scalable deployment of high‑density AI compute.
The ideal candidate brings an engineering‑first mindset, strong expertise in modular and liquid‑cooled data centers, GPU‑based systems, and the energy, curiosity, and positivity required to thrive in fast‑moving and ambiguous environments. This role is instrumental in driving adoption, trust, and long‑term customer success.
Location: Remote
Location: Remote
Key Responsibilities
Core Technical Customer Engagement
- Serve as the primary technical partner between customers and Armada’s Product and Engineering teams, translating real‑world requirements into actionable designs.
- Provide hands‑on technical guidance on AI Factory solutions, including modular and liquid‑cooled data centers and NVIDIA‑based GPU systems.
- Advise customers on workload suitability, rack‑level design, system architecture, and deployment tradeoffs.
- Lead technical demos, proofs‑of‑concept, and working sessions tailored to customer environments and constraints.
- Build trusted‑advisor relationships with engineering, infrastructure, IT, OT, and security stakeholders.
- Enable Sales and field teams by distilling complex infrastructure topics into clear, outcome‑driven narratives.
- Take end‑to‑end ownership of technical engagements, bringing curiosity, urgency, and a problem‑solving mindset.
Required Qualifications & Technical Expertise
- Bachelor’s degree in Engineering, Computer Science, or related field (or equivalent hands‑on experience); advanced degrees a plus.
- 5+ years of experience in data center engineering, infrastructure engineering, pre‑sales/sales engineering, or solution architecture.
- Strong foundation in compute, networking, and storage, including GPU‑based AI systems (e.g., NVIDIA DGX, HGX, MGX).
- Hands‑on experience with data center infrastructure, including MEP systems, cooling architectures, and rack‑level design.
- Deep familiarity with modular and/or liquid‑cooled data center architectures, power density, and thermal management.
- Ability to translate AI workload requirements into scalable, production‑ready infrastructure designs.
- Working knowledge of cloud platforms, containerization, virtualization, and modern enterprise infrastructure.
- Comfort operating in complex, live customer environments, with strong troubleshooting skills.
- Ability to build credibility across IT and OT stakeholders, particularly in industrial or energy‑adjacent contexts.
- Excellent communication skills, capable of engaging both deeply technical teams and executive audiences.
- Willingness to travel as required.
Nice to Have:
- Exposure to energy, utilities, telecom, oil & gas, or industrial infrastructure environments.
- Understanding of power generation, distribution, or energy‑driven deployments.
- Familiarity with AI data center co‑location or Neocloud models.
- Experience with regulated or mission‑critical systems and structured sales methodologies (e.g., MEDDPICC, Challenger).