Summer 2026 Intern, AI Engineer

Ryan•Plano, TX

About The Position

We are seeking an AI Engineer Intern interested in building and advancing agentic AI systems that power next-generation products. In this role, you will work alongside a team of engineers and subject matter experts to design, develop, and deploy intelligent systems that automate complex workflows and enhance decision-making. You will gain hands-on experience working with cutting-edge AI technologies, including large language models (LLMs), retrieval-augmented generation (RAG), and multi-agent systems, while contributing to solutions used by real clients.

Requirements

Working toward a Bachelor’s or Master’s degree in Computer Science or Artificial Intelligence.
Anticipated graduation date within one year of internship
Minimum Overall and Major GPA of 2.8
Minimum of 6 – 12 Accounting or technical hours depending on practice
Experience with Python and software development best practices
Familiarity with large language models (LLMs) and model APIs (e.g., OpenAI, Anthropic, Google)
Strong problem-solving and analytical skills with attention to detail
Ability to work in a fast-paced, innovative environment and manage multiple priorities
Strong written and verbal communication skills
Ability to work both independently and collaboratively within a team environment
Demonstrated curiosity and interest in emerging AI technologies and trends
Intermediate knowledge of all Microsoft Office applications, Outlook, and etc.
To perform this job successfully, an individual must have knowledge of Python and familiarity with modern development tools and environments.
Valid driver's license required.

Nice To Haves

Exposure to retrieval systems, machine learning concepts, or AI application development preferred
Experience with version control systems (e.g., Git), APIs, and cloud-based platforms is preferred.
Also, an individual must have intermediate knowledge of Microsoft® Word, Access, Excel, PowerPoint, Outlook, and Internet navigation and research.

Responsibilities

Design, develop, and implement agentic AI systems, including multi-step workflows, tool-calling, and multi-agent coordination
Build and optimize retrieval-augmented generation (RAG) pipelines, including chunking strategies, embedding models, and search methodologies
Develop and maintain evaluation frameworks to measure system performance, accuracy, and reliability
Conduct rapid prototyping and experimentation to evaluate new models, tools, and architectural approaches
Integrate LLM APIs into production systems, including handling structured outputs, retries, and performance optimization
Implement AI safety and trust mechanisms, including validation, monitoring, and human-in-the-loop processes
Analyze system performance, identify issues, and iterate on solutions using data-driven approaches
Collaborate with cross-functional teams to deliver scalable and reliable AI-powered solutions