AI Information Security Engineer - Southern New Hampshire University

Southern New Hampshire University is a team of innovators. World changers. Individuals who believe in progress with purpose. Since 1932, our people-centered strategy has defined us — and helped us grow a team that now serves over 180,000 learners worldwide.

Our mission to transform lives is made possible by talented people who bring diverse industry experience, backgrounds and skills to the university. And today, we're ready to expand our reach. All we need is you.

Make an impact — from near or far

At SNHU, you'll have the option to work remotely in the following states: Alabama, Arizona, Arkansas, Delaware, Florida, Georgia, Hawaii, Idaho, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Mississippi, Missouri, Nebraska, New Hampshire, New Mexico, North Carolina, North Dakota, Ohio, Oklahoma, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, West Virginia, Wisconsin and Wyoming.

We ask that our remote employees have access to a reliable internet connection and a dedicated, properly equipped workspace that is free of distractions. Employees must reside in, and work from, one of the above approved states.

The opportunity

The AI Security Engineer will report to the Director of Information Security Engineering. You will be hands-on security engineering role responsible for securing AI systems, models, and agent-based workloads throughout development. You will focus on practical threat modeling, control implementation, testing, and monitoring to protect AI training data, inference pipelines, agents, tools, and generated outputs from misuse, compromise, or unintended harm. You will partner with AI engineering, platform, and security teams to ensure AI systems are secure by design, resilient to misuse, and observable in production at scale.

You will work 100% remotely from any of our approved states.

What You'll Do:

• Document AI system components and data flows, including prompts, context, embeddings, training data, model artifacts, outputs, and agent tool interactions.
• In collaboration with the AI team, identify attack surfaces, trust boundaries, and privilege transitions within AI pipelines and agent workflows and perform structured threat modeling for AI systems during design, development, and change cycles in collaboration with the AI team.
• In collaboration with the AI team, translate identified threats into concrete, relevant security requirements and engineering tasks in collaboration with the AI team.
• Implement technical controls informed by established AI security frameworks (e.g., OWASP LLM Top 10, NIST AI RMF) according to compliance requirements and AI governance guidance.
• Design, build, and maintain automated security testing for AI systems within CI/CD pipelines, supports testing for prompt injection, unsafe model behavior, misconfigured ac