AI Deployment Program Lead - Data Center (Nordics)

Dell Inc.; Oslo fylke; On-site; NOK 900,000 - 1,300,000; Full time

Job summary

Dell Technologies ISG is seeking an experienced AI Project Program Manager to orchestrate end-to-end deployment projects in data center environments across the Nordics. You will lead GPU and network rack installations on-site, ensuring projects meet contracted outcomes on time and within budget.

In this role, you will partner with customers and internal teams to translate scope into realized outcomes, apply predictive risk insights, and leverage AI-forward methods to improve delivery accuracy

Qualifications

• 7+ years in project or program management within technology services, IT infrastructure deployment, or data center operations.
• Exceptional communication, coordination, and stakeholder management skills.
• Willingness to travel frequently to customer data center sites across EMEA (Nordics and Iceland).

Responsibilities

• Lead deployment activities at customer data centers, including GPU, network, and large-scale compute rack installations.
• Serve as the customer's trusted advisor and onsite contact for deployment status, risk escalation, and issue resolution across logistics, installation, and construction readiness.
• Drive disciplined scope management with formal change requests and align delivery objectives across teams.
• Deploy predictive risk insights to identify early warning signals and protect delivery timelines.

Skills

Project management

Stakeholder management

Communication

Onsite leadership

Travel readiness

Risk management

Job description

Dell Technologies ISG is seeking an experienced AI Project Program Manager to orchestrate end-to-end deployment projects in data center environments across the Nordics. You will lead GPU and network rack installations on-site, ensuring projects meet contracted outcomes on time and within budget.

In this role, you will partner with customers and internal teams to translate scope into realized outcomes, apply predictive risk insights, and leverage AI-forward methods to improve delivery accuracy