AI/ML Engineer
Listed on 2026-08-26
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Software Development
AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Nelnet is a diversified and innovative company committed to enriching lives through the power of service as a student loan servicer, professional services company, consumer loan originator and servicer, payments processor, renewable energy solutions, and K-12 and higher education expert. For over 40 years, Nelnet has been serving its customers, associates, and communities. The perks of working at Nelnet go beyond our benefits package.
When you join the Nelnet team, you're part of a community invested in the success of each individual. That support comes through in our work, as we are united by our mission of creating opportunities for people where they live, learn, and work. At Nelnet, we believe in the transformative power of data and technology to drive business innovation.
Our AI / ML Engineer role sits at the center of that work: building, operating, and scaling the AI agents that automate processes, surface insights, and help our teams make better decisions faster. If you're passionate about taking agentic systems from prototype to dependable production capability, we invite you to join our team and help shape how AI gets used across our business.
This posting covers multiple levels within the AI / ML Engineer role. We are currently seeking candidates at the equivalent of a Level I or II AI / ML Engineer. The responsibilities and qualifications below describe the full scope of the role; expectations for depth, autonomy, and scope of ownership will vary by level. Level and corresponding compensation are determined during the interview process based on demonstrated experience.
We encourage you to apply if you meet the core qualifications, even if you don't match every item listed.
As an AI / ML Engineer at Nelnet, you'll be at the intersection of applied AI and software engineering. Your primary focus will be twofold: keeping our existing fleet of deployed agents healthy, evaluated, and improving over time, and designing new agentic capabilities that extend what those systems can do. Beyond building, you'll help expand the agentic approach across the organization, partnering with business stakeholders to identify high-value use cases, establishing reusable patterns and guardrails, and raising the bar for how teams evaluate and ship AI systems.
You'll collaborate closely with Data Scientists, Product, Software Engineers, and business partners to move solutions from concept to production.
Design, build, and deploy LLM-powered agents to solve concrete business problems. This includes tool use, multi-step reasoning, orchestration, and human-in-the-loop patterns.
Own the day-to-day health of agents already in production: monitor behavior, diagnose failures, tune prompts and tooling, and manage model and dependency upgrades without regressing quality.
Build and maintain evaluation suites for agent systems, including offline test sets, LLM-as-judge scoring, regression testing, and online metrics.
Instrument agents end to end, including traces, tool calls, token usage, latency, cost, and outcome quality and act on what the data shows.
Design retrieval and context strategies (RAG, structured data access, caching, chunking, ranking) that give agents the right information at the right time.
Build and maintain the tools, APIs, and connectors agents rely on, ensuring safe and reliable interaction with internal systems and data.
Design and implement scalable AI pipelines and services on AWS, using infrastructure as code (Terraform) and CI/CD to automate deployment and maintenance.
Implement safety controls, input/output validation, access boundaries, and audit trails appropriate to a regulated environment.
Partner with teams across the organization to identify where agents add real value, prototype quickly, and turn one-off wins into reusable frameworks and standards.
Maintain clear documentation of agent architectures,…
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