AI-Enabled Requirements Engineering Intern

About the Role

• Company: Space Dynamics Laboratory (SDL)
• Program: Internship Program
• Division: Strategic Military Space Division
• Location: North Logan, UT
• Term: Summer of 2027 (up to 12 weeks)
• Start Date: No later than Monday, June 7th

Key Responsibilities

• Evaluates supervised uses of AI tools to extract and organize requirements from approved, non-sensitive example artifacts.
• Helps prototype a process for proposing requirement-to-verification links in a Requirements Verification Traceability Matrix (RVTM), with human review of all outputs.
• Compares AI-assisted results with manually prepared examples for accuracy, completeness, and traceability.
• Documents limitations, quality checks, data-handling considerations, and recommended validation steps.
• Presents a demonstration and findings to the systems engineering team.
• Contributes to a cloud-based enterprise ground system supporting dynamic space operations.

Requirements & Tech Stack

• Education:
• Currently pursuing an undergraduate or graduate degree in systems, aerospace, mechanical, electrical, computer engineering, computer science, or a closely related field.
• Minimum 3.0 GPA.
• Skills & Experience:
• Basic understanding of engineering requirements, data analysis, or software development.
• Experience with a programming or scripting language through coursework or projects.
• Ability to evaluate technical outputs critically and document repeatable results.
• Ability to work collaboratively with engineers and other interns and independently with appropriate guidance.
• Strong initiative, attention to detail, and written and verbal communication skills.
• Citizenship & Clearance:
• Must be a U.S. citizen.
• Ability to obtain and maintain a U.S. Government security clearance.

Desired Qualifications

• Experience with Python, spreadsheets, structured data, or basic natural language processing (NLP).
• Exposure to requirements traceability, verification planning, or engineering data management.
• Familiarity with responsible AI practices, including human validation and approved-data handling.