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AI Engineer
Career Insights for Natural Language Processing Engineer
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Based on Nebraska data
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What they do
A Natural Language Processing Engineer specializes in developing and implementing algorithms and models tailored for understanding, processing, and generating natural language text. They utilize methodologies such as tokenization, parsing, named entity recognition, part-of-speech tagging, and other NLP techniques to perform tasks including text classification, chatbot development, and other applications where the primary input or output is natural language text.
$120,811 / year median in Nebraska
Job Description
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.- Role Overview
- As an AI Engineer at Nelnet, you'll be at the intersection of applied AI and software engineering.
- Job Responsibilities
- 1.
- Agent Development
- : 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. 2.
- Operating the Existing Fleet
- : 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. 3.
- Evaluation
- : Build and maintain evaluation suites for agent systems, including offline test sets, LLM-as-judge scoring, regression testing, and online metrics. 4.
- Observability and Monitoring
- : Instrument agents end to end, including traces, tool calls, token usage, latency, cost, and outcome quality and act on what the data shows. 5.
- Context and Retrieval Engineering
- : Design retrieval and context strategies (RAG, structured data access, caching, chunking, ranking) that give agents the right information at the right time. 6.
- Tooling and Integrations
- : Build and maintain the tools, APIs, and connectors agents rely on, ensuring safe and reliable interaction with internal systems and data. 7.
- Scalability and Infrastructure
- : Design and implement scalable AI pipelines and services on AWS, using infrastructure as code (Terraform) and CI/CD to automate deployment and maintenance. 8.
- Guardrails and Responsible AI
- : Implement safety controls, input/output validation, access boundaries, and audit trails appropriate to a regulated environment. 9.
- Expanding Agentic Adoption
- : 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. 10.
- Documentation
- : Maintain clear documentation of agent architectures, prompts, tool contracts, data flows, evaluation results, and known limitations. 11.
- Innovation
- : Track the fast-moving foundation model and agent tooling landscape, and bring what's genuinely useful into our stack. 12.
- Mentorship
- : Provide guidance to team members on agent design, evaluation practices, and applied AI best practices.
- Key Competencies
- 1.
- At this time, we are unable to consider external candidates that reside in these states: Alabama, California, Connecticut, Hawaii, Illinois, Maine, Massachusetts, Michigan, New Jersey, New York, Oregon, Rhode Island, Vermont, Washington.
- Qualifications
- Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field (or equivalent experience).
- U.S. Citizenship AND the ability to obtain a U.S. 6C Security Clearance.
- Minimum of 2 years of experience in machine learning engineering, AI engineering, software engineering, or related roles.
- Demonstrated experience building agentic systems with large language models. Examples include tool calling, orchestration, multi-step workflows - not just single-turn prompting.
- Hands-on experience evaluating LLM and agent systems, including designing eval sets and interpreting results to drive iteration.
- Experience deploying and supporting AI or ML systems in production environments.
- Experience with retrieval-augmented generation and other approaches to grounding models in enterprise data.
- Starting Salary Range for this
Role:
$95k - 130k- Our benefits package includes medical, dental, vision, HSA and FSA, generous earned time off, 401K/student loan repayment, life insurance & AD&D insurance, employee assistance program, employee stock purchase program, tuition reimbursement, performance-based incentive pay, short- and long-term disability, and a robust wellness program.
Privacy Policy and Pre-Use Notice:
Automated Tools in Hiring You may know Nelnet as the nation's largest student loan servicer - but we do more than that. _A lot more._ We're also a professional services company, consumer loan originator and servicer, payment processor, renewable energy innovator, and K-12 and higher education expert (and that's just a shortlist). For over 40 years, we've been serving our customers, associates, and communities to make dreams possible. EEO Info (https://nelnetinc.com/wp-content/uploads/EEO-poster.pdf) | EEO Letter (https://nelnet.com/wp-content/uploads/EEO-Jeffs-Letter.pdf) | EPPA Info (https://nelnetinc.com/wp-content/uploads/Employee-Polygraph-Protection-Act-Poster.pdf) | FMLA Info (https://nelnetinc.com/wp-content/uploads/FMLA-Leave.pdf)Benefits
- Financial Aid/Assistance
- 401(k) Plans
- Employee Stock Options (ESOs)
- Health and Wellness Programs