AI Security Analyst

Summary

The client is a research, recruiting, licensing, education, and entrepreneurship organization that provides AI services to students, faculty, and staff for teaching, research, and university operations. The AI Security Analyst will evaluate AI platforms, integrations, and agentic systems for security risks, recommend controls and decisions, advise technical teams, and develop scalable secure AI practices.

Responsibilities

• AI Security Analyst
• Client IT provides AI services to 110K students, faculty, and staff for teaching, research, and university operations
• These services include Cloudforce’s nebulaONE multi-model AI platform hosted in Microsoft Foundry, commercial LLM offerings such as Microsoft Copilot, ChatGPT EDU, Claude EDU, and Google Gemini Enterprise, connectors and plugins, an AI gateway (in procurement), and other associated components (e.g. MCP servers)
• This position will be responsible for evaluating the security of the AI services to identify risks, recommending compensating controls and new security products, advising the teams on AI-specific security topics, and helping build knowledge in secure AI practices
• Platform & integration risk evaluation
• Evaluate new releases and capabilities across AI platforms and tools for security risks — including nebulaONE, the ChatGPT/Claude/Gemini/Copilot EDU instances, and agentic AI platforms
• Evaluate integrations, connectors, and plug-ins linking AI tools to university data sources such as Microsoft 365, enterprise systems, and enterprise databases
• Assess agentic-specific risks — standing credentials, autonomous tool access, and data exfiltration by agents — as capabilities that warrant distinct scrutiny
• Risk assessment & decision authority
• Supply AI-specific threat expertise within the university's tiered AI risk assessment process
• Recommend go/no-go decisions and escalate to Information Security’s Director or Consulting and Architecture and CISO based on the scope, scale, and data sensitivity of the system
• Advisory
• Advise the AI team on security questions
• Advise on AI architecture to ensure security is considered and integrated
• Advise on security tooling to strengthen the AI ecosystem
• Advise on vendor and third-party risk, including data processing agreements, SOC 2 reports, data residency, and sub-processors
• Building leverage (scaling expertise beyond individual assessments)
• Enhance AI security knowledge and advisory capabilities within the existing team
• Define reusable secure baselines and reference configurations for each AI platform so guidance can be applied without per-case involvement
• Ground recommendations in recognized frameworks — NIST AI RMF, the OWASP Top 10 for LLMs, and MITRE ATLAS
• Staying current
• Track the evolving AI threat landscape — new attack techniques, platform changes, and emerging standards — and fold changes into assessments and baselines

Skills

• Bachelor's degree in Cybersecurity, Computer Science, Engineering, or a related field, or equivalent experience
• 3+ years of experience in cybersecurity, application security, cloud security, or related technical security roles
• Hands-on experience with AI/ML systems, LLM applications, or data pipelines
• Strong understanding of secure coding, authentication, authorization, API security, and cloud security
• Familiarity with adversarial ML concepts, model security, and AI risk management
• Experience securing generative AI applications, RAG systems, or model serving platforms
• Familiarity with frameworks and guidance such as OWASP Top 10 for LLM Applications, OWASP Top 10 for Agentic * Applications, NIST AI RMF, or MITRE ATLAS
• Working knowledge of at least two compliance frameworks: FERPA, HIPAA, NIST 800-53/800-171, or SOC 2
• Understanding of privacy, data governance, and regulatory considerations for AI
• Relevant certifications such as CISSP, GSEC, CSSLP, AWS Security Specialty, or similar

Qualifications

Must Haves

• Bachelor's degree in Cybersecurity, Computer Science, Engineering, or a related field, or equivalent experience
• 3+ years of experience in cybersecurity, application security, cloud security, or related technical security roles
• Hands-on experience with AI/ML systems, LLM applications, or data pipelines
• Strong understanding of secure coding, authentication, authorization, API security, and cloud security
• Familiarity with adversarial ML concepts, model security, and AI risk management

Nice to Haves

• Experience securing generative AI applications, RAG systems, or model serving platforms
• Familiarity with frameworks and guidance such as OWASP Top 10 for LLM Applications, OWASP Top 10 for Agentic * Applications, NIST AI RMF, or MITRE ATLAS
• Working knowledge of at least two compliance frameworks: FERPA, HIPAA, NIST 800-53/800-171, or SOC 2
• Understanding of privacy, data governance, and regulatory considerations for AI
• Relevant certifications such as CISSP, GSEC, CSSLP, AWS Security Specialty, or similar

Benefits

• Health Benefits
• Referral Program
• Excellent growth and advancement opportunities
• Remote work