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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Infrastructure Delivery Engineer Graduate (Server Delivery) - 2027 Start - **Company:** BYTEDANCE INC. - **Location:** San Jose, CA, United States - **Experience:** Starter - **Salary:** $76,000.0 - $128,000.0 - **Contract:** Permanent contract - **Skills:** Microsoft Excel, Artificial Intelligence, Big Data, Cloud Computing, Computer Clusters, Data Centers, Python (Programming Language), Cloud Services, SQL Databases, AI Infrastructure, Data Processing, Scripting, AI Platforms, Information Technology, Hardware Infrastructure - **Published:** August 3, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=695404c8f29fcd0a ## About the Role * 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, Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment ## Description 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., 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., * 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. 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