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AI Infrastructure DC Design Intern

Astreya82 open roles

Where
Remote, CA
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Your applicationOpen nowAI Infrastructure DC Design InternAstreya · Remote, CA
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10.1% of postings close within 7 days. Measured by our own scanner across the market. Astreya postings stay open a median of 5 days.

Share of postings closed within
  1. 2.0%1 day
  2. 4.0%3 days
  3. 10.1%7 days
  4. 15.7%14 days
  5. 34.0%30 days
This job: posted yesterday

Astreya median: 5 days open

The posting

AI Infrastructure Datacenter Design Engineer Intern

Position Summary

The AI Infrastructure Datacenter Design Engineer Intern supports the engineering team in basic data hall design, documentation, and infrastructure planning activities while gaining hands-on experience in AI and hyperscale data center environments. This role is designed for students or recent graduates looking to develop foundational knowledge in datacenter infrastructure, AutoCAD drafting, rack layouts, cabling standards, and engineering project coordination under the guidance of senior engineers.

Key Responsibilities

● Assist in creating and updating AutoCAD drawings, rack elevations, cabinet layouts, and structured cabling documentation. ● Support data hall design documentation, asset tracking, and revision management activities. ● Assist engineering teams with infrastructure inventory validation and basic capacity tracking. ● Help maintain design standards, templates, and project documentation repositories. ● Participate in engineering reviews, design walkthroughs, and quality assurance activities. ● Coordinate with cross-functional teams to gather project inputs and update design records. ● Support preparation of project reports, spreadsheets, diagrams, and technical documentation. ● Learn data center infrastructure concepts including power, cooling, cabling, rack configurations, and AI cluster environments. ● Follow established operational procedures, engineering standards, and safety requirements. ● Assist with administrative and project coordination tasks related to infrastructure deployment activities.

Learning Opportunities

● Exposure to AI and hyperscale data center infrastructure environments. ● Hands-on experience with AutoCAD and infrastructure design tools. ● Understanding of structured cabling, rack layouts, and datacenter operational workflows. ● Participation in real-world engineering and infrastructure deployment projects. ● Mentorship from senior engineering and infrastructure professionals. ● Exposure to project management, documentation control, and engineering lifecycle processes.

Scope & Complexity

● Works on low-complexity assignments with clearly defined objectives and supervision. ● Primarily focused on learning, documentation support, and foundational engineering tasks. ● Limited independent decision-making authority. ● Collaborates closely with engineering, operations, and project teams.

Requirements

● Currently pursuing or recently completed an Associate or Bachelor’s degree in Engineering, Information Technology, Computer Science, or related field. ● Basic understanding of datacenter or IT infrastructure concepts preferred. ● Familiarity with AutoCAD, Visio, or similar drafting/documentation tools is a plus. ● Proficiency in Microsoft Office tools including Excel, PowerPoint, and Word. ● Strong attention to detail, organization, and communication skills. ● Ability to learn quickly and work in a collaborative team environment. ● Interest in AI infrastructure, data centers, networking, or cloud technologies preferred.

Salary Range

$15.71 - $24.81 USD (Hourly)

  • Please note that the salary information provided herein is base pay only (gross); it does not include other forms of compensation which may or may not apply to this specific position, namely, performance-based bonuses, benefits-related payments, or other general incentives - none of which are guaranteed, may be subject to specific eligibility requirements, and are wholly within the discretion of Astreya to remit.
  • Further, the salary information noted above is a range that consists of a minimum and maximum rate of pay for this specific position. Where an applicant or employee is placed on this range will depend and be contingent on objective, documented work-related considerations like education, experience, certifications, licenses, preferred qualifications, among other factors.
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