## About the Role

Nelnet is hiring an AI FinOps Engineer to own token economics and cost optimization for its Enterprise AI program. The role sits in Shared Services and reports to the IT Director of AI Delivery, with an initial focus on Anthropic Claude and the broader EA portfolio.

This is a hands-on technical position that works at the API level to instrument workloads, uncover inefficiencies, and reduce cost without sacrificing capability. It also turns token-level analysis into practical guidance that the AI enablement team can share across the organization.

The annual compensation range for this position is $100,000 to $150,000, depending on experience. It includes a hybrid work option for associates living within 30 miles of an office location, with remote work available part of the week and in-office collaboration three days per week.

## Key Responsibilities

– Track, model, and optimize token costs across enterprise AI platforms.
– Improve prompt efficiency, caching strategies, and model-tier selection guidance.
– Build and maintain dashboards for usage trends, cost anomalies, and efficiency metrics for IT leadership.
– Identify waste, recommend tier or model changes, quantify savings, and carry recommendations through implementation.
– Document token optimization best practices and partner with the AI enablement team on organization-wide guidance.

## Required Skills

– 1–2 years of hands-on experience with LLM APIs such as Claude, OpenAI, or equivalent, including token-level optimization.
– Strong understanding of LLM pricing mechanics, including context windows, caching, batching, input/output token splits, and tier structures.
– Experience with prompt engineering focused on efficiency and cost reduction.
– Proficiency in Python or SQL for instrumentation and pipeline work.
– Ability to communicate technical findings to non-technical stakeholders.

## Preferred Skills

– 2–4 years of industry experience.
– Experience with prompt caching, batch API usage, or model-tier switching in production.
– Cloud FinOps experience or FinOps Foundation certification.
– Experience working with multiple LLM providers and comparing cost and capability tradeoffs.

## Cloud Platforms & Technologies

### AI / LLM Platforms & Features
– Anthropic Claude
– OpenAI
– LLM APIs
– Prompt caching
– Batch API usage
– Model-tier switching

### Programming Languages
– Python
– SQL

### Reporting / BI
– Dashboards

## FinOps Responsibilities

– Track and model token costs across enterprise AI platforms.
– Optimize prompt efficiency, caching, and model selection to reduce spend.
– Build reporting on usage trends, cost anomalies, and efficiency metrics.
– Identify waste, quantify savings, and guide implementation of recommended changes.
– Translate analysis into best practices for broader organizational use.

## Benefits

– Medical, dental, and vision coverage
– HSA and FSA options
– Generous earned time off
– 401(k) and student loan repayment
– Life insurance and AD&D coverage
– Employee assistance program
– Employee stock purchase program
– Tuition reimbursement
– Performance-based incentive pay
– Short- and long-term disability coverage
– Wellness program

## Why You Might Be Interested

This role gives you direct ownership of AI cost efficiency in a setting where measurement, optimization, and reporting all matter. It combines hands-on technical work with the opportunity to influence broader internal guidance. If you want to work closely with both engineers and non-technical stakeholders while shaping how enterprise AI spend is managed, this position offers that scope. The hybrid schedule and stated compensation range add further clarity for candidates evaluating the opportunity.