
AI Security Engineer
SNHU Careers
full-time
Posted on:
Location Type: Remote
Location: Alabama • Arizona • United States
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Salary
💰 $94,130 - $150,634 per year
Tech Stack
About the role
- 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
- 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
- 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
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
AI security frameworksthreat modelingautomated security testingCI/CD pipelinessecurity controlsruntime safeguardsidentity managementaccess controlinput validationoutput filtering