Forward Deploy Engineer

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 modular edge data centers powered by the Armada Edge Platform, and Leviathan, Armada’s AI Factory, which partners with Bridge, our GPU-as-a-Service offering. Together, these capabilities enable enterprises and governments to deploy, operate, and scale AI workloads securely, efficiently, and close to where data is generated.

Saudi Arabia is Armada’s operational anchor for the ME region. As we scale, we are intentionally building a team of senior, versatile operators who can both get systems live and own customers long-term. This role is designed for engineers who want full lifecycle ownership, not narrow scope.

Role Overview

The Senior Forward Deploy Engineer is a hybrid role responsible for hands-on deployment execution and ongoing technical account ownership for Armada customers across ME. This role combines the intensity and depth of a Forward Deploy Engineer with the long-term customer ownership of a Technical Account Manager.

In the early phases of customer engagement, this role leads deployments, platform bring-up, and initial workload execution. Once customers are live, the same engineer remains the primary technical owner, driving adoption, operational maturity, and expansion.

This role reports into the Sr. Director of Customer Success & Delivery, EMEA & ANZ and is intentionally designed to avoid split ownership between deployment and post-sale success. Success is measured by speed to production, customer confidence, platform adoption, retention, and expansion.

Key Responsibilities

Deployment execution and platform bring-up

• Lead end-to-end deployment of Armada platforms including Atlas, Galleon with AEP, and Leviathan AI Factory integrated with Bridge GPU-as-a-Service
• Own on-site and in-country deployments across Saudi Arabia and the broader ME region
• Own infrastructure bring-up, platform configuration, and production readiness validation
• Make real-time technical decisions across hardware, networking, Kubernetes, storage, and GPU layers

Technical account ownership and customer success

• Own the long-term technical relationship with assigned customers post-deployment
• Drive platform adoption, workload onboarding, and operational maturity
• Identify expansion opportunities and work with customers to scale their AI infrastructure
• Serve as the primary technical point of contact for customer escalations and operational issues