VP, Customer Engineering

Armada is seeking a visionary VP of Customer Engineering & Value Engineering (Global) to lead a world-class, globally distributed organization 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, commercial execution, and large-scale industrial deployment.

This leader will own and scale both the Customer Engineering (CE) and Value Engineering (VE) functions globally, ensuring tight integration between technical discovery, solution architecture, and business value articulation across the entire pre-sales lifecycle.

As Armada accelerates adoption of its AI-powered edge platform—spanning ruggedized modular data centers, GPU-accelerated inference, and real-time edge AI—this role will define how we engage with customers worldwide. From initial technical discovery through validated, deployment-ready architectures and quantified business outcomes, you will drive a consistent and high-impact motion across North America, EMEA, APAC, and emerging markets.

The combined CE + VE organization 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 technical and business requirements

Framing AI infrastructure trade-offs

Validating feasibility and ROI

Ensuring full qualification prior to deep engineering engagement

You will build a best-in-class global pre-sales engine where:

Customer Engineering drives technical discovery and architecture

Value Engineering quantifies ROI, operational impact, and strategic value

Together, they accelerate revenue while enforcing discipline, consistency, and scale

What You'll Do

Build & Scale a Global Customer Engineering & Value Engineering Organization

Lead, coach, and develop a globally distributed team across North America, EMEA, APAC, and emerging markets

Own global hiring strategy across Customer Engineering and Value Engineering, building presence in new regions and scaling existing teams

Establish operating rhythms, onboarding frameworks, and standards for technical and commercial excellence worldwide

Create career pathways that develop Customer Engineers into AI infrastructure architects and Value Engineers into strategic advisors

Build a culture of continuous learning across AI, edge computing, and industrial deployments at scale

Drive AI-Focused Technical Discovery & Value-Based Solutioning

Champion a rigorous AI-first discovery methodology, integrating both technical and value-based frameworks

Guide teams to uncover:

AI workload requirements

Business drivers and ROI levers

Data sovereignty and regulatory constraints

Connectivity realities across global environments

Ensure translation of complex environments into:

Validated edge architectures (Galleon, Atlas, GPU stack)

Clear economic value propositions and business cases

Define standards for:

AI inference, real-time analytics, and ML pipelines

Value quantification, ROI modeling, and executive-level narratives

Elevate Global Pre-Sales Excellence (Technical + Value)

Set the global bar for:

Architecture quality

Discovery rigor

Value articulation

Proof-of-value frameworks

Standardize technical and commercial qualification frameworks ensuring opportunities are:

Technically feasible

Economically justified

Strategically aligned

Implement global review cadences combining:

Architecture validation (CE)

Business case validation (VE)

Drive consistency across regions while maintaining local adaptability

Partner Cross-Functionally to Accelerate Global Revenue

Collaborate with Sales, Product, Engineering, and Deployment teams globally

Align technical architectures with business outcomes, including:

ROI

Operational efficiency

AI-driven transformation

Partner closely with verticals including energy, defense, telecom, and industrials

Feed global insights into:

Product roadmap

Hardware evolution

Platform strategy

Build Scalable Methodologies & Playbooks

Develop globally consistent:

AI edge reference architectures

ROI frameworks and value playbooks

Proof-of-value methodologies

Create repeatable patterns across:

GPU deployments

Hybrid edge-cloud architectures

Satellite-connected environments

Enable regional teams with:

Localized regulatory and deployment considerations

Partner ecosystem integration

Balance global consistency with regional agility

Core Skills & Capabilities

Global Leadership & Team Development

Proven experience building and scaling global CE and/or VE organizations

Strong talent builder with ability to develop technical and commercial leaders

Ability to operate in ambiguity and bring structure to high-growth environments

Experience working across international markets, enterprises, and governments

AI Infrastructure & Edge Architecture

Deep expertise in:

GPU compute and AI inference

Distributed systems and edge computing

LLM and ML deployment

Strong understanding of infrastructure trade-offs:

Latency vs bandwidth

Edge vs cloud

Sovereignty vs scale

System Architecture & Engineering Design

Ability to architect end-to-end systems across:

Modular data centers

Networking, storage, compute

Fluency in:

Engineering documentation

Deployment planning

Real-world infrastructure constraints

Value Engineering & Strategic Storytelling

Strong ability to:

Build ROI models and business cases

Translate technical solutions into executive value

Influence C-level stakeholders

Expertise in commercial positioning and competitive differentiation

Required Qualifications

Bachelor’s degree in a relevant technical field

7+ years leading Customer Engineering, Solutions Architecture, or Value Engineering teams globally

7–10+ years in pre-sales, AI infrastructure, data center, or distributed systems

GPU infrastructure (NVIDIA ecosystem)

AI frameworks (TensorRT, ONNX, etc.)

Datacenter and edge architecture

Experience with:

Kubernetes, virtualization, cloud (IaaS/PaaS)

Proven ability to influence C-level stakeholders globally

Willingness to travel internationally, including remote/field environments

Preferred Qualifications

Experience in energy, defense, telecom, utilities, or industrial sectors

Exposure to modular/mobile data centers

Edge AI optimization

OT/IT convergence

Satellite/LEO connectivity (Starlink, VSAT)

Global experience across EMEA, APAC, or Middle East

Relevant certifications (AI/ML, cloud, datacenter)

Compensation & Benefits

For U.S. Based candidates: To ensure fairness and transparency, the on-target earnings salary range for this role for candidates in the U.S. are listed, varying based on location experience, skills, and qualifications. In addition to the salary, this role will also be offered equity and subsidized benefits (details available upon request).