Agentic Development Intern

Carnegie Mellon University•Pittsburgh, PA

10d•Onsite

About The Position

The Agentic Development Intern will work within the Cyber Mission Readiness Directorate in CERT, collaborating with software engineers, learning engineers, and cybersecurity experts who build software and automation for cyber training, exercises, and assessments. The intern will assist the Operational Readiness and Evaluation team in developing agentic AI workflows to research, generate, and review curriculum with source traceability and human approval built in. They will build and maintain GitOps pipelines for linting, testing, packaging, and deploying training content, web applications, and virtual lab environments, and research and prototype automation approaches using AI and traditional software engineering practices to deliver reliable, repeatable systems. The internship begins in Fall 2026, with an option to continue through the Spring 2027 semester. It is a part-time, fully onsite position based in the Pittsburgh office. The work includes agentic AI workflow development and evaluation; CI/CD and GitOps automation; infrastructure as code and containerized environments; and test automation and developer tooling.

Requirements

Be enrolled in a degree-granting program.
Be willing to travel to various locations to support the SEI’s overall mission, including within the SEI and CMU community.
Be eligible to work in the United States without visa sponsorship and submit to a background check.
Have the ability to think critically and solve problems.
Be familiar with a programming or scripting language, such as Python, JavaScript/TypeScript, or Bash.
Be familiar with Git and collaborative workflows, such as branching and merge requests.
Have basic knowledge of Linux, the command line, and containers such as Docker.
Be able to collaborate with professional engineers, instructional designers, and subject matter experts, internally and externally.
Be willing to learn new technologies with cross-functional teams.
Be organized and detail-oriented, and able to clearly document and communicate findings.

Nice To Haves

Experience building with large language model APIs or agent frameworks, including tool use or Model Context Protocol (MCP).
Experience with CI/CD platforms such as GitLab CI or GitHub Actions.
Experience with infrastructure as code or GitOps tools such as Terraform, Packer, Ansible, or Argo CD.
Experience writing automated unit, integration, or end-to-end tests. These experiences may come from education-driven experiences or extracurricular activities.

Responsibilities

Design, build, and evaluate agentic AI workflows with human review checkpoints.
Develop and maintain CI/CD pipelines and GitOps automation.
Develop infrastructure as code and containerized environments for training and labs.
Write tests and documentation, and demonstrate solutions to the team.
Research and prototype automation approaches using AI and traditional software engineering practices.
Assist in creating workflows to research, generate, and review curriculum with source traceability and human approval.
Build and maintain pipelines that lint, test, package, and deploy training content, web applications, and virtual lab environments.