Intern - AI Engineer

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Yes, we’re a student loan servicer. We’re also a technology company, idea incubator, start-up accelerator, and K-12 and higher education expert. At Nelnet, we’re so much more than what you think—and we’re just getting started. So, no matter what you want to do in life—build codes or build brands—we’re the best place to do it.

Join Nelnet as an intern and do real work that matters to our business. All Nelnet interns receive one-on-one mentorship, competitive pay, casual dress, flexible schedule, intern-specific programming, and meaningful work experience.

Apply to one of our internships today. Your career awaits.

Nelnet's AI Lab is building the agent frameworks, integrations, and technical infrastructure that will define how Nelnet operates with AI over the next several years. AI Engineer Interns join a small, high-velocity team doing that work directly: building and testing agents, exploring LLM-based workflows, researching emerging frameworks, and contributing to production-bound tooling.

Help build, test, and iterate on AI agents using the team's secure agent framework. This includes working with LLM APIs, multi-agent orchestration patterns, and tooling that runs in Nelnet's Microsoft 365 and cloud environment.

Track developments in LLM frameworks, agent architectures, tooling, and industry approaches. Evaluate options against the team's real constraints (security, identity, M365 integration) and surface findings with clear "so what" framing. Research here feeds real decisions, not slide decks.

Build proof-of-concept integrations between LLM-based systems and Nelnet's internal tools and APIs. Test assumptions early, document what worked and what didn’t, and hand off something the team can build on.

Document design decisions, system behavior, and implementation notes with the precision of someone who expects a future engineer to read it. Participate in code review as both author and reviewer.

Present your work, findings, and recommendations to AI Lab leadership and team members at the end of the internship period.

Pursuing a degree in Computer Science, Software Engineering, Data Science, or a related technical field.

We care more about what you've built than which courses you've taken. A strong portfolio of personal projects, open-source contributions, or prior technical internships carries more weight than GPA alone.

Has used LLMs for real technical work, not just experimentation. This might mean using Claude or ChatGPT to write, debug, or extend code; building a personal project with an LLM API; or integrating AI tooling into a workflow. Can speak concretely about what they built, how it worked, and what the limits were.

Python is the primary language. Solid working knowledge is required. Experience with any of the following is a strong plus:
Lang Chain, Lang Graph, Claude API, OpenAI/Claude SDK, FastAPI, or similar frameworks. Familiarity with REST APIs, JSON, and basic cloud or serverless patterns is beneficial.

Personal projects, research, coursework projects, or prior internships that involved building something end-to-end. We want to see evidence of independently scoped and completed technical work, however small.

Experience working on a team where requirements weren't perfectly defined. Comfortable asking clarifying questions, proposing solutions, and moving forward without waiting for perfect information.

• LLM Fluency: Uses LLMs as a genuine engineering tool, not just a novelty. Understands prompt construction, context windows, tool use, and the failure modes that matter in production. Knows when to reach for an LLM and when not to.
• Agentic Systems Thinking: Understands how business workflows can be decomposed into agentic patterns: what an agent owns, what it delegates, what triggers it, and where it can fail. Asks the right questions about data access, identity, security, and trust before assuming the happy…