Loyola Marymount University is hiring for a one-year fixed term Senior AI Security Analyst role based in Los Angeles, CA (onsite). In this position, you will use an offensive mindset to find weaknesses, strengthen AI systems, and embed intelligent automation across the security practice. You will work closely with security, applications, and infrastructure teams to securely configure and monitor AI tools and services.
Compensation for this contract opportunity is USD 89,100 - 120,400 per year, with salary commensurate with education and experience.
What you will do
- Leverage AI for SOC automation and alert tuning using Microsoft tools including Defender, Sentinel, Entra, and Copilot.
- Implement AI-powered threat detection and security monitoring across endpoints, networks, cloud infrastructure, and applications.
- Participate in security assessments, vulnerability testing, and threat simulations with approved tools and methodologies.
- Use AI-enabled security tooling to help identify potential vulnerabilities and security gaps.
- Evaluate security risk and compliance considerations for AI-enabled applications, APIs, and related technologies.
- Develop and maintain security controls, detection logic, and monitoring capabilities to identify misuse or compromise of AI systems.
- Support security configuration, policy enforcement, and access controls for organizational AI tools such as Copilot, Microsoft 365 Copilot, internal LLM chatbots, and third-party AI APIs.
- Support implementation and monitoring of data loss prevention (DLP) controls tied to approved AI technologies.
- Track emerging CVEs, research publications, and AI security threat intelligence, translating findings into actionable mitigations.
- Embed security checkpoints into AI-augmented development workflows, including scanning and reviewing code generated by tools such as Copilot.
- Shift AI-assisted security testing left with the applications team to reduce cost and impact of vulnerabilities found later in the SDLC.
- Evaluate, implement, and optimize cloud threat protection using AWS GuardDuty and Microsoft Defender for Cloud, including cross-platform configuration and integration.
- Strengthen cloud security posture using AWS Security Hub, Microsoft Defender, and AWS Inspector to identify, prioritize, and remediate vulnerabilities for cloud and serverless workloads.
- Expand cloud asset tagging, classification, and workload identification to improve inventory, ownership, visibility, and risk management.
- Develop security automation for incident response and remediation, including automated agent deployment and updates, control enforcement, and alert notifications.
- Strengthen cloud identity and access management through least-privilege access controls, AWS IAM Access Analyzer, role governance, and periodic access reviews.
- Implement and optimize web application security controls including AWS WAF to protect cloud-hosted applications and APIs.
- Assess the effectiveness of existing security controls and recommend improvements based on threat intelligence, incidents, vulnerability trends, and technology changes.
- Conduct threat hunting using telemetry, indicators of compromise, behavioral analytics, and AI-powered detection capabilities.
- Partner with university stakeholders to advance AI security, controls, and compliance.
- Support the university mission through behavior aligned to its vision and values, and demonstrate high standards of professional, responsible, accountable, and ethical conduct, including strong customer service.
Required qualifications
- Typically a bachelor’s degree or equivalent experience in computer science, information systems management, business administration, or a related field.
- Relevant certifications: OSCP, CEH, CISSP, or emerging AI security credentials (CompTIA SecAI) a plus.
- Minimum 3 years of cybersecurity, information security, or security operations experience.
- Consecutive hands-on experience configuring and managing network security systems, application, web, database, and end-point security technologies, including firewalls, IDS/IPS, SIEM, and end-point security.
- Experience using or supporting AI-enabled technologies and familiarity with associated security and governance considerations.
- Experience with Microsoft Defender, Copilot, and AWS cloud.
- Knowledge of AI governance frameworks such as NIST AI RMF, ISO 42001, or the EU AI Act.
- Familiarity with MLOps pipelines, model registries, and security considerations for deploying AI in production.
- Background in threat intelligence or adversarial machine learning research.
- Strong organizational, analytical, and problem-solving skills, with the ability to manage multiple priorities.
- Excellent written and verbal communication skills for engaging technical and non-technical stakeholders and building collaborative relationships.
- Demonstrated ability to work independently and within cross-functional teams, supporting successful project outcomes.
Tools and technologies
Microsoft Defender, Microsoft Sentinel, Microsoft Entra, Copilot, Microsoft 365 Copilot, AWS GuardDuty, Microsoft Defender for Cloud, AWS Security Hub, AWS Inspector, AWS IAM Access Analyzer, AWS WAF, SIEM, IDS/IPS, DLP (data loss prevention), NIST AI RMF, ISO 42001, EU AI Act, MLOps pipelines, model registries, OSCP, CEH, CISSP, CompTIA SecAI.
