Senior Customer Solutions Engineer, AI Factory, ANZ

About Armada

Armada delivers sovereign, industrial-grade AI infrastructure designed to operate where traditional cloud and centralized data center models fall short. Our platform includes Atlas as the control plane, Galleon rugged, containerized and modular edge data centers powered by the Armada Edge Platform, and Leviathan, Armada's AI Factory, and Bridge, our GPU-as-a-Service offering. Together, these capabilities enable enterprises and governments to deploy, operate, and scale AI and other HPC workloads securely and efficiently across highly regulated and mission-critical environments.

ANZ is a core growth region for Armada, spanning large enterprises, public sector customers, and infrastructure-heavy industries. Leviathan is Armada's purpose-built AI Factory. A high-density GPU compute platform designed for neocloud operators, sovereign AI programs, and enterprises building or expanding large-scale AI infrastructure capacity. Customers in this space require a senior technical partner who understands the economics, operations, and architecture of GPU-dense environments and can drive successful long-term outcomes at scale.

Role Overview

The Senior Customer Solutions Engineer, AI Infrastructure for ANZ is a senior technical role responsible for driving successful deployment and long-term adoption of Armada's Leviathan AI Factory platform. This role is built for operators who understand GPU infrastructure at in depth, from physical deployment and power and cooling constraints to AI workload offtake, colocation agreements, and sovereign AI program requirements.

This role serves customers in neocloud operations, hyperscale AI infrastructure, colocation, and sovereign AI environments. Segments where GPU availability, infrastructure density, operational reliability, and commercial offtake structures are the defining decision factors. The Senior CSE owns the full technical relationship: from initial solution design and facility readiness through cluster commissioning, workload onboarding, and ongoing capacity expansion.

This role reports into the VP Global Customer Success & Delivery. Success is measured by Leviathan deployment velocity, GPU cluster utilization, capacity expansion, and the depth of technical partnership with AI infrastructure operators across ANZ.

Key Responsibilities

Leviathan AI Factory deployment and commissioning

• Lead end-to-end AI workload activation on Armada's Leviathan AI Factory platform, driving GPU cluster onboarding, workload configuration, and production readiness from initial capacity commitment through sustained offtake utilization

• Own infrastructure commissioning across GPU compute, high-speed networking (InfiniBand, RoCE), NVMe storage, and out-of-band management layers

• Make real-time technical decisions across hardware, firmware, networking, and orchestration layers during deployment and early operations

• Partner with customers and facility operators to validate power, cooling, and physical infrastructure requirements ahead of Leviathan deployments

• Conduct facility readiness assessments and pre-deployment site surveys to surface risk and ensure frictionless cluster commissioning

Technical account ownership and customer success

• Serve as the primary technical point of contact for assigned AI infrastructure accounts post go-live

• Own the technical success plan, GPU utilization milestones, and operational maturity roadmap for each customer

• Build trusted, long-term relationships with infrastructure operators, ML platform engineers, procurement leads, and executive stakeholders

• Lead technical governance discussions, capacity planning reviews, and platform optimization conversations; collaborate with AEs to deliver QBRs

• Act as the primary technical escalation contact during incidents or performance issues

Joint Success Plan ownership

• Build, maintain, and actively drive Joint Success Plans (JSPs) for each assigned customer

• Align deployment milestones, GPU utilization targets, and capacity expansion to customer business objectives and offtake commitments

• Use the Joint Success Plan as the primary framework for prioritization, execution, risk management, and value tracking

• Regularly review progress against success plans with customer stakeholders and Armada leadership

• Ensure JSPs inform deployment sequencing, cluster expansion strategy, roadmap discussions, and commercial offtake planning

• Surface risks, dependencies, and blockers early and drive resolution with clear ownership

Capacity expansion and AI infrastructure offtake

• Accelerate time-to-value by driving rapid GPU cluster commissioning and workload onboarding, from initial bring-up through sustained production utilization

• Drive Leviathan capacity expansion across additional clusters, racks, and facilities as customer AI workload demand grows

• Identify and pursue expansion opportunities including additional Leviathan deployments, Bridge GPUaaS offtake, and Atlas-managed multi-site configurations

• Collaborate with customers on AI infrastructure offtake planning, helping translate training, inference, and HPC workload requirements into infrastructure capacity decisions

Operational excellence and reliability

• Ensure customer GPU environments remain stable, performant, and production-ready at scale

• Proactively identify scaling risks, thermal constraints, networking bottlenecks, and GPU utilization gaps

• Coordinate with Product, Engineering, and Support teams to resolve issues efficiently and feed learnings back into platform development

Data residency, security, and regulatory execution

• Operate confidently within ANZ data residency, sovereignty, and security requirements relevant to AI infrastructure deployments

• Support customer security reviews, audits, and governance processes in regulated and sovereign AI environments

• Balance global delivery standards with regional regulatory requirements, including export controls and data localization obligations

• Maintain disciplined access control, documentation, and operational hygiene across customer environments

Field leadership and mentorship

• Act as a senior technical presence for ANZ AI infrastructure accounts, setting the bar for deployment quality and customer engagement

• Mentor (junior) CSEs, and delivery engineers as the region and Leviathan customer base scales

• Contribute to deployment standards, commissioning runbooks, and repeatable best practices for GPU cluster environments

Cross-functional collaboration

• Partner closely with the VP, Global Customer Success & Delivery on priorities and escalations

• Work with Sales on capacity expansion and offtake planning while maintaining a trusted post-sale technical posture

• Provide structured feedback to Product and Engineering teams based on real customer GPU infrastructure deployments and operational patterns

Qualifications and Experience

• 8+ years of experience in data center operations, GPU infrastructure engineering, solutions engineering, or technical customer-facing roles in AI or HPC infrastructure

• Hands-on experience deploying and operating GPU clusters at scale, including familiarity with NVIDIA GPU architectures, InfiniBand or RoCE networking, NVMe-oF storage, and BMC/out-of-band management

• Background in neocloud operations, AI factory deployment, or hyperscale data center environments, with understanding of the commercial and operational dynamics of large-scale GPU infrastructure

• Experience with AI infrastructure offtake models, including GPUaaS, reserved capacity, and co-location or build-to-suit arrangements

• Demonstrated ability to own the full customer technical lifecycle - from solution scoping and cluster commissioning through capacity expansion and long-term account ownership

• Willingness to travel across ANZ as required for deployments, site surveys, and customer engagements

• Clear, confident communication style suited for both hands-on infrastructure engineers and C-suite stakeholders in AI infrastructure organizations

Preferred Experience

• Direct experience with neocloud or AI factory build-outs, including multi-tenant GPU infrastructure, shared fabric networking, and facility power and cooling design for high-density compute

• Familiarity with sovereign AI programs, government AI infrastructure mandates, or regulated AI compute environments requiring data localization and export compliance

• Experience in colocation or hyperscale infrastructure contexts, including cage/suite design, interconnect provisioning, and power capacity planning

• Knowledge of AI/ML training and inference infrastructure patterns, including large model parallelism, distributed training frameworks (PyTorch, JAX), and inference serving platforms

• Solutions architecture or pre-sales engineering background, with ability to translate AI workload requirements and offtake commitments into infrastructure deployment and capacity plans

• Comfort operating with ambiguity and owning outcomes end to end in a fast-moving, high-growth environment

What Success Looks Like

• Leviathan AI Factory clusters are commissioned rapidly and reach target GPU utilization benchmarks on schedule

• AI infrastructure customers, neoclouds, sovereign AI programs, and hyperscalers, operate with high confidence in Armada's platform reliability and the Senior CSE's technical ownership

• Capacity expands across clusters, facilities, and offtake agreements without handoff friction or account fragmentation

• Customers in neocloud, colocation, and sovereign AI environments view Armada as the strategic GPU infrastructure partner for their most demanding compute requirements

• Adoption grows across Leviathan deployments, Bridge GPUaaS offtake, and Atlas-managed multi-site configurations driven by the Senior CSE's deep technical engagement

• Customers view Armada as a long-term infrastructure partner via consistency of technical ownership delivered at every stage of the relationship