AI Security Engineer

SNHU Careers

. Document AI system components and data flows, including prompts, context, embeddings, training data, model artifacts, outputs, and agent tool interactions.

Posted 4/3/2026full-timeRemote • Alabama, Arizona, Florida, Hawaii, Idaho, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Mississippi, Missouri, Montana, New Hampshire, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, West Virginia, Wisconsin, Wyoming • 🇺🇸 United StatesMid-LevelSenior💰 $94,130 - $150,634 per yearWebsite

Tech Stack

Tools & technologies

Cyber Security

About the role

Key responsibilities & impact

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.
In collaboration with the AI team, translate identified threats into concrete, relevant security requirements and engineering tasks.
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 access, data exposure, and agent misuse.
Ensure AI security controls are validated during build, deployment, and change cycles, with failures surfaced early to engineering teams.
Implement technical guardrails to protect sensitive data used by AI systems.
Design and operate controls for sensitive data identification, minimization, redaction, and leakage prevention.
Design, implement, and maintain security controls across the full AI/ML lifecycle.
Implement and operate runtime safeguards for AI services and agent-based systems.
Design security controls that balance safety, system performance, reliability, and developer usability in production of AI services.
Implement and operate secure identity, secrets, and access control patterns for AI services.

Requirements

What you’ll need

5+ years of experience in IT or cybersecurity, with engineering responsibilities (i.e. IT Security or Application Development)
2 + years of experience securing AI/ML systems or adjacent domains with demonstrated application to AI workloads.
Experience with security engineering principles, including authentication, authorization, logging, and monitoring.
Experience with AI/ML concepts such as models, training data, inference pipelines, embeddings, and agent frameworks.
Experience modeling data flows, trust boundaries, and attack paths in AI systems.
Experience mitigating threats such as prompt injection, model poisoning, model theft, and data leakage.
Experience implementing controls such as input validation, output filtering, context isolation, and abuse detection.

Benefits

Comp & perks

High-quality, low-deductible medical insurance
Low to no-cost dental and vision plans
5 weeks of paid time off (plus almost a dozen paid holidays)
Employer-funded retirement
Free tuition program
Parental leave
Mental health and wellbeing resources

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

AI security frameworksthreat modelingautomated security testingCI/CD pipelinessecurity controlsruntime safeguardsidentity managementaccess controlinput validationoutput filtering