Infrastructure Delivery Engineer Graduate - Server Delivery

The Global Server Delivery team builds and scales the physical infrastructure that powers the next generation of AI. Every year, we deploy gigawatts (GW) of compute capacity across global data centers, delivering thousands of CPU and GPU servers to support large-scale AI and cloud services. Our team owns the end-to-end delivery lifecycle, including new platform introduction, infrastructure planning, power and cooling optimization, deployment execution, and operational readiness. We focus on maximizing power utilization, improving delivery efficiency, and ensuring the highest standards of quality and reliability. By combining engineering expertise with AI-driven analytics and automation, we continuously optimize infrastructure planning and operations at global scale. We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume. Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early. You will work at the intersection of AI infrastructure, large-scale server deployment, data center engineering, and intelligent operations. This role offers the opportunity to participate in the deployment of next-generation AI/GPU clusters that power large-scale cloud and AI services. Rather than focusing on a single discipline, you will collaborate with hardware, networking, facilities, supply chain, software, and operations teams to deliver thousands of servers into production efficiently and reliably. As AI becomes an essential engineering tool, 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. 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