Technology AI Intern - Summer 2026

Salas O'Brien • Boulder, CO

2d • Onsite

About The Position

At Salas O'Brien, we're dedicated to engineering for impact. Our mission to make a difference is at the core of everything we do, from our projects to our team culture. We strive to embody values of inspiration, achievement, and connection, fostering collective ownership and a sustainable future. Established in 1975, Salas O'Brien is an employee-owned engineering and professional services firm focused on creating impact for our clients, team members, and the world. We know that today’s challenges bring tomorrow’s opportunities, and we’re here to design innovative, lasting solutions. We specialize in creating environments where people connect, perform, and thrive. Our team consults on projects ranging from performing arts centers and universities to corporate campuses, cultural venues, and entertainment destinations. By integrating technology, acoustics, and theatre systems, we help clients deliver experiences that inspire and engage.

As a Technology AI Intern, you will gain practical experience developing and evaluating AI-powered tools that enhance engineering workflows for our Technology and Acoustics (TAC) Group. This role focuses on building internal prototypes, creating prompt libraries, and establishing best practices for generative AI use in technical design environments. You'll collaborate with seasoned engineers on real projects spanning data centers, healthcare facilities, educational institutions, sports venues, performing arts venues, and entertainment destinations. If you're ready to apply AI capabilities to solve practical engineering challenges and learn from industry leaders, we encourage you to apply.

Requirements

• Currently enrolled in a Bachelor’s or Master’s degree program in Computer Science, Computer Engineering, Engineering Design, Data Science, or a related technical field.
• Demonstrated practical experience building with large language models through coursework, personal projects, hackathons, or previous internships (e.g., prompt design, basic evaluation, or application integration).
• Strong communication skills with the ability to collaborate effectively within a team environment.
• Passionate about Audio/Video, Lighting Design and Consultation, Cabling Infrastructure, and Security Systems, and eager to learn and contribute to create impactful AI tools.
• Adaptable to shifting priorities and tasks, with readiness to perform duties onsite as required.
• Demonstrated practical experience building with large language models through coursework, personal projects, hackathons, or previous internships (e.g., prompt design, basic evaluation, or application integration).

Nice To Haves

• Programming experience in Python or JavaScript, including familiarity with APIs, data handling (CSV, JSON, databases), and version control systems (Git).
• Awareness of AI risk considerations including data privacy, bias mitigation, hallucination detection, and responsible AI practices.
• Exposure to audiovisual systems, IT infrastructure, structured cabling, building automation, or security systems through coursework, personal interest, or previous experience.
• Understanding of engineering workflows, technical documentation standards, or design processes in architecture, engineering, or construction (AEC) industries.
• Previous internship or co-op experience in AI, software development, or technical consulting environments.

Responsibilities

• Design and build AI-enabled workflow prototypes for TAC engineers, such as specification summarization tools, RFP requirement extraction utilities, or equipment database query assistants.
• Develop and maintain prompt engineering playbooks and templates for common engineering tasks, including guardrails, example inputs/outputs, and usage guidelines documented in a shared repository.
• Create evaluation frameworks for AI-generated outputs, including accuracy verification methods, hallucination detection approaches, citation traceability systems, and quality benchmarks tailored to engineering documentation.
• Partner with project teams across diverse facility types to gather requirements, define success criteria (time saved, error reduction, usability improvements), and conduct user testing of AI tools.
• Conduct research on emerging generative AI trends, model capabilities, and integration patterns relevant to engineering workflows, and present findings to the TAC team.
• Track tool usage, effectiveness, and user feedback to iterate on AI solutions and inform adoption strategies.
• Document all developed tools with clear usage instructions, limitations, risk considerations (privacy, bias, hallucinations), and maintenance requirements.

What This Job Offers

• Career Level: Intern