Infrastructure Delivery Engineer Graduate

About the Role

This role offers the opportunity to work at the intersection of AI infrastructure, large-scale server deployment, data center engineering, and intelligent operations. You will participate in the deployment of next-generation AI/GPU clusters that power large-scale cloud and AI services. You will collaborate with hardware, networking, facilities, supply chain, software, and operations teams to deliver thousands of servers into production efficiently and reliably. You will also leverage AI technologies to automate planning, perform large-scale data analysis, generate operational insights, and improve engineering productivity.

Key Responsibilities

• AI Infrastructure Delivery:
• Participate in the deployment of next-generation CPU and GPU server platforms.
• Learn server architecture, hardware components, power characteristics, and deployment requirements.
• Support new platform introduction (NPI), system compatibility validation, and deployment readiness.
• Assist in large-scale server rollout projects across global data centers.
• Capacity Planning & Engineering Analysis:
• Analyze server power consumption, rack capacity, cooling requirements, and infrastructure utilization.
• Support capacity planning for data centers based on electrical and thermal constraints.
• Build analytical models to optimize rack layouts, deployment efficiency, and resource utilization.
• Identify operational risks and recommend engineering improvements.
• Project & Operations Management:
• Coordinate cross-functional teams including engineering, supply chain, facilities, vendors, and operations.
• Track project schedules, deployment milestones, and delivery quality.
• Manage deployment readiness, installation progress, and engineering documentation.
• Support material planning and accessory management for large-scale deployments.
• AI-driven Engineering:
• Apply AI tools to improve engineering workflows.
• Use AI to automate data processing, reporting, documentation, and root cause analysis.
• Analyze millions of operational records to identify trends, anomalies, and optimization opportunities.
• Explore AI-assisted capacity forecasting, deployment planning, and intelligent operations.

Requirements & Tech Stack

• Minimum Qualifications:
• Individuals who are completing or have recently completed a Bachelor's or Master's degree in Computer Science, a similar technical field of study, or equivalent practical experience.
• Strong analytical and problem-solving skills.
• Curious mindset with willingness to learn complex systems.
• Good communication and teamwork skills.
• Comfortable working with data and solving engineering problems.
• Preferred Qualifications (Experience in one or more of the following is a plus):
• Python, SQL, or scripting languages
• Excel data analysis and visualization
• AI tools
• Data center infrastructure
• Server hardware
• Cloud computing