CyberSecurity AI Engineer

Job Summary

Nelnet is seeking a Security Engineer with expertise in AI/ML to build secure, compliant AI solutions in partnership with IT, security, and data science teams. The role requires deep technical knowledge, sound judgment, and a proactive approach to risk management.

• Monitor and strengthen the security posture of AI/ML systems, APIs, and model‑serving environments.
• Build detection and monitoring capabilities to identify risks such as model misuse, prompt injection, data poisoning, and unauthorized model access.
• Partner with development, operations, and security teams to secure AI environments throughout their full lifecycle.
• Automate security monitoring and remediation workflows for AI systems.
• Evaluate and implement AI security tools and model‑governance solutions.
• Contribute to the development of AI‑specific risk frameworks, controls, and policies.
• Stay current on the evolving AI risk landscape and support security assessments and testing of LLMs and AI services.
• Conduct security testing and threat modeling for AI systems.
• Support logging, monitoring, and alerting for AI/ML environments integrated with SIEM/XDR platforms.
• Help design model access controls, encryption, and governance enforcement.
• Assist in developing and enforcing AI‑related security policies and procedures.
• Question legacy assumptions and recommend AI‑native security approaches.
• Build security prototypes and proof‑of‑concepts for emerging AI architectures.
• Navigate ambiguity in AI risk management and compliance requirements.
• Investigate security incidents involving AI‑generated outputs or manipulated inputs.
• Apply critical thinking to defend against emerging AI risks and develop layered mitigation strategies across models, APIs, and infrastructure.
• Own problem resolution from start to finish.
• Partner with Cyber Security analysts, developers, and AI engineers to defend AI systems.
• Mentor peers on emerging risks and best practices in AI/ML security.
• Translate technical AI security issues into business risk language for stakeholders.
• Write clear documentation for detection rules, playbooks, and findings.
• Present AI risk scenarios and mitigation strategies to both technical and non‑technical audiences.
• Align AI security efforts with Nelnet's business, compliance, and technology goals.
• Serve as a trusted advisor on AI governance, LLM access, and model risk.
• Anticipate future regulatory requirements around AI usage and safety.
• Deliver security solutions that balance innovation with operational integrity.

$115,000 – $155,000, dependent on experience and education.

• Education:
  
  Equivalent to a Bachelor's degree in Computer Science or related field.
• Experience:
  
  3 to 5 years in cybersecurity, security engineering, or risk management.
• Hands‑on experience with machine learning systems, LLMs (Anthropic Claude, OpenAI, or open‑source models), or AI/ML platforms such as Sage Maker, Azure ML, or Vertex AI.
• Familiarity with adversarial machine learning concepts and model risk.
• Experience with security tools, monitoring platforms, or security automation frameworks.
• Experience in application security, Dev Sec Ops , or secure software development life cycle (SDLC) is a plus.
• Programming skills in Python or a similar language.
• Knowledge of AI‑specific risk frameworks such as MITRE ATLAS or the OWASP LLM Top 10.
• Strong analytical skills and comfort working with data, logs, and system telemetry.
• Ability to work across teams and lead cross‑functional security initiatives.
• Familiarity with regulations governing IT environments and ethical frameworks around AI security and model governance.

• Security, controls, and computer technology knowledge.
• Leadership and motivation of others.
• Statistical and probabilistic analysis for identifying problems, trends, and relationships.
• Knowledge of at least one computer development language and related methodologies.
• Understanding of AI system architectures and their security implications.
• Ability to assess and communicate risk and urgency clearly to both management and engineering staff.
• Strong organizational, presentation, verbal, and written communication skills.
• Ability to adjust…