AI Factory Customer Engineer (City of Gold Coast)

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 Key Responsibilities
- 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.
- 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). Armada is seeking a visionary VP of Customer Engineering to lead a world‑class, globally distributed team of Customer Engineers at the forefront of AI infrastructure and edge computing. This is a pivotal leadership role for a builder and operator who thrives at the intersection of cutting‑edge AI technology and large‑scale industrial deployment. As Armada accelerates adoption of its AI‑powered edge platform spanning ruggedized modular data centers, GPU‑accelerated inference, and real‑time edge AI this leader will shape how we engage with customers globally: from initial technical discovery through validated, deployment‑ready architectures. You will own the pre‑sales technical lifecycle across all regions, ensuring our Customer Engineers operate with rigor, speed, and clarity in North America, EMEA, APAC, and emerging markets. The CE function guides customers from mission‑critical AI ambitions and complex operational environments to scalable, field‑proven Armada solutions taking each opportunity 80% of the way by scoping requirements, framing AI infrastructure trade‑offs, validating feasibility, and ensuring full qualification before moving to detailed engineering. What You’ll Do Build & Scale a Global Customer Engineering Organization
- Lead, coach, and develop a globally distributed team of Customer Engineers spanning North America, EMEA, and emerging markets.
- Define and execute a global hiring strategy: build CE presence in new regions, establish operating rhythms, onboard early hires, and set standards for technical excellence worldwide.
- Create talent development pathways that grow CEs into senior AI infrastructure architects and future leaders.
- Build a culture of continuous learning around AI infrastructure, edge computing, and real‑world deployment at scale. Drive AI‑Focused Technical Discovery & Solution Architecture
- Champion a rigorous, AI‑first discovery methodology guiding CEs to uncover customer mission goals, AI workload requirements, data sovereignty constraints, and connectivity realities across diverse global environments.
- Ensure the team consistently translates complex, distributed AI environments into validated edge architectures built around Armada's Galleon modular data centers, Atlas platform, and GPU‑accelerated edge AI stack.
- Define and govern solution design standards for AI inference, real‑time analytics, and edge ML pipelines in bandwidth‑constrained and disconnected environments. Elevate Global Pre‑Sales Technical Quality
- Set and raise the bar on discovery outputs, AI architecture designs, technical narratives, demo environments, and proof‑of‑value success criteria worldwide.
- Standardize technical qualification frameworks ensuring AI infrastructure opportunities are well‑scoped, feasible, and commercially validated before deep engineering engagement.
- Develop a global review cadence and peer architecture process to maintain consistency and quality across all regions. Partner Cross‑Functionally to Accelerate Global Revenue
- Collaborate tightly with regional Sales leaders, Product, Engineering, and Global Deployment teams to align on AI infrastructure positioning, competitive differentiation, and customer roadmaps.
- Bridge technical architectures to measurable customer outcomes articulating ROI, operational efficiency, and AI‑driven value creation across energy, defense, telecommunications, and industrial verticals.
- Synthesize global customer insights to inform Armada's AI product roadmap, hardware evolution, and platform strategy. Build Scalable AI Infrastructure Methodologies & Playbooks
- Develop globally consistent reference architectures for AI inference at the edge, GPU cluster deployments, satellite‑connected operations, and hybrid cloud‑edge patterns.
- Create repeatable frameworks for AI proof‑of‑value pilots, technical discovery, and competitive positioning across Armada's key verticals.
- Enable regional CE teams with localized deployment guides, regulatory considerations, and partner ecosystem alignment — ensuring global consistency while preserving local agility. System Architecture & Engineering Design
- Translate mission and business objectives including AI workload requirements — into actionable infrastructure requirements aligned to operational outcomes.
- Architect end‑to‑end systems within modular or containerized data centers, integrating GPU compute, high‑speed storage, and networking into defined form factors.
- Interpret engineering documentation including rack elevations, BOMs, airflow diagrams, and power schematics; create conceptual architecture drawings for customers and partners.
- Perform on‑site assessments and deployment planning, incorporating power, cooling, physical security, and connectivity constraints across global environments. Technical Strategy & Competitive Positioning
- Expert technical storyteller: frames AI infrastructure trade‑offs, simplifies complexity, and aligns diverse technical and executive stakeholders toward confident decisions.
- Deep understanding of real‑world AI deployment constraints: thermal limits, bandwidth scarcity, satellite connectivity, mobile power, and austere environments.
- Competitive intelligence and positioning across edge AI, cloud infrastructure, and industrial IoT markets. Required Qualifications
- Bachelor's degree in Computer Science, Electrical Engineering, Systems Engineering, or equivalent technical field.
- 7+ years leading Customer Engineering or Solutions Architecture teams in pre‑sales; demonstrated success hiring and scaling globally.
- 7–10+ years of hands‑on pre‑sales or solutions engineering experience in AI infrastructure, edge computing, …