AI Factory Customer Engineer at Armada

, , Australia -

Full Time

Start Date

Immediate

Expiry Date

05 Jul, 26

Salary

0.0

Posted On

06 Apr, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI Infrastructure, Edge Computing, GPU Systems, Data Center Engineering, Solution Architecture, Pre-sales Engineering, Modular Data Centers, Liquid Cooling, Kubernetes, NVIDIA DGX, System Architecture, Technical Leadership, Cloud Platforms, Virtualization, Infrastructure Design, Strategic Partnerships

Industry

Software Development

Description

About the Company Armada is a full-stack edge infrastructure company delivering compute, connectivity, and sovereign AI/ML to some of the world’s most remote places. Named one of Fast Company's Most Innovative Companies, Armada’s solutions are deployed in over 60 countries globally for organizations ranging from energy to defense. With over $200 million in funding, Armada is backed by top investors such as Microsoft (M12), Founders Fund, and has strategic partnerships including Starlink, Skydio, and NVIDIA. We are looking for the most brilliant minds in the world to join us. Working at Armada means taking ownership, driving autonomy, and delivering impact. You’ll tackle challenges that haven’t been solved before and help build something transformative from the ground up. What you do here will not only define your career but help further Armada’s mission to bridge the digital divide for customers around the world. 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 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). 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. Core Skills & Capabilities Global Leadership & Team Development Proven ability to build, lead, and scale Customer Engineering teams across multiple geographies — hiring in new markets and establishing regional functions from the ground up. Strong coaching and talent development instincts: grows senior AI infrastructure architects and cultivates future technical leaders. Operates with clarity and conviction in ambiguous, high-growth environments creates structure and alignment for globally distributed teams. Culturally fluent and experienced working across diverse international stakeholders including enterprise customers, governments, and strategic partners. AI Infrastructure & Edge Architecture Deep expertise in GPU-accelerated compute, AI inference pipelines, LLM deployment, and ML workloads in resource-constrained environments. Strong architectural fluency across edge computing, modular/containerized data centers, distributed systems, and AI platform integration. Practical knowledge of AI infrastructure trade-offs: latency vs. bandwidth, on-device vs. cloud inference, sovereignty vs. scale, and power density vs. performance. Familiarity with MLOps, AI observability, and model lifecycle management in edge and hybrid environments. 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, datacenter, or distributed systems. Deep expertise in GPU and AI accelerator infrastructure: NVIDIA GPU architectures, AI inference frameworks (TensorRT, ONNX, vLLM), and edge AI platforms. Strong grounding in datacenter and edge infrastructure: compute (GPU, bare metal, virtualization), storage (SAN/NAS/Object/NVMe), networking (LAN/WAN/SD-WAN/SATCOM), and facility systems (power, cooling). Hands-on experience with container orchestration (Kubernetes), virtualization (VMware, KVM, Hyper-V), and cloud service models (IaaS, PaaS, hybrid). Proven ability to engage and influence C-level technical and operational leaders across global enterprise and government customers. Willingness to travel internationally, including to remote and operationally austere field sites. Preferred Qualifications Experience deploying or architecting AI solutions in oil & gas, defense & intelligence, utilities, telecommunications, or mining verticals. Hands-on exposure to modular, containerized, or mobile data center deployments — including skid-based and rapid-deploy form factors. Familiarity with edge AI inference optimization, model quantization, and deployment frameworks for bandwidth-constrained environments. Background integrating OT/IT convergence — connecting sensors, IIoT devices, and SCADA systems to AI-enabled edge platforms. Experience with satellite and hybrid connectivity architectures (Starlink, LEO, VSAT) for remote AI deployments. International experience building CE teams or managing customer engagements in EMEA, APAC, or Middle East markets. Certifications in AI/ML (e.g., NVIDIA DLI), cloud infrastructure (AWS, Azure, GCP), or datacenter design (CDCP, DCDC, RCDD). Experience collaborating with construction, facilities, and deployment partners on large-scale infrastructure projects. #LI-Remote You're a Great Fit if You're A go-getter with a growth mindset. You're intellectually curious, have strong business acumen, and actively seek opportunities to build relevant skills and knowledge A detail-oriented problem-solver. You can independently gather information, solve problems efficiently, and deliver results with a "get-it-done" attitude Thrive in a fast-paced environment. You're energized by an entrepreneurial spirit, capable of working quickly, and excited to contribute to a growing company A collaborative team player. You focus on business success and are motivated by team accomplishment vs personal agenda Highly organized and results-driven. Strong prioritization skills and a dedicated work ethic are essential for you Equal Opportunity Statement At Armada, we are committed to fostering a work environment where everyone is given equal opportunities to thrive. As an equal opportunity employer, we strictly prohibit discrimination or harassment based on race, color, gender, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other characteristic protected by law. This policy applies to all employment decisions, including hiring, promotions, and compensation. Our hiring is guided by qualifications, merit, and the business needs at the time. Unsolicited Resumes and Candidates Armada does not accept unsolicited resumes or candidate submissions from external agencies or recruiters. All candidates must apply directly through our careers page. Any resumes submitted by agencies without a prior signed agreement will be considered unsolicited and Armada will not be obligated to pay any fees.

Responsibilities

The role involves building and scaling a global team of Customer Engineers to drive AI infrastructure adoption and technical discovery. You will partner with cross-functional teams to translate complex customer requirements into validated, scalable edge AI architectures.