Cybersecurity Analyst - AI

The AI Cybersecurity Analyst role connects artificial intelligence initiatives with robust digital defense, focusing on building machine learning based threat detection, auditing AI systems for vulnerabilities, and driving automated incident response across enterprise environments.

Responsibilities

• AI Threat Modeling: Develop and implement threat models for AI pipelines, leveraging MITRE ATLAS to uncover data poisoning, model inversion, and model theft risks.
• Secure AI Architecture: Collaborate with engineering teams to implement secure-by-default AI designs, establish guardrails, and protect data confidentiality and integrity.
• AI-Driven Detection: Deploy and optimize AI and ML tools for automated threat detection, log analysis, and incident response to counter AI fueled attacks.
• Model Monitoring: Establish real-time monitoring to identify anomalies in neural network outputs or data quality that signal potential compromise.
• AI Governance, Risk & Compliance: Align AI development lifecycles with frameworks such as the NIST AI Risk Management Framework and OWASP AI Security guidelines.
• AI Tooling Development: Design, build, and deploy AI powered cybersecurity tools for threat detection, vulnerability assessment, and incident response.
• Threat Analysis with ML: Apply machine learning algorithms to analyze network traffic, logs, and security alerts for immediate threat identification.
• Security Controls and Compliance: Implement and manage controls in line with NIST, ISO 27000 series, and FedRAMP to ensure broad system compliance.
• Vulnerability Research: Conduct assessments across IT infrastructure including LAN, WAN, SAN, and cloud environments such as AWS and Google Cloud Platform.
• Security Device Management: Configure and maintain devices like Cisco ISE, Cisco ASA, IDS/IPS, VPNs, and SIEM platforms such as Splunk or New Relic for continuous monitoring.
• Incident Response Leadership: Lead response efforts by analyzing attack frameworks with threat intelligence, executing recovery plans, and documenting security plans.

Requirements

• Bachelor's or Master's degree in Computer Science, Cybersecurity, Data Science, or a related STEM field.
• Minimum 3 years of AI cybersecurity experience required.
• At least 3 years in AI architecture and AI governance required.
• Nine years of cybersecurity engineering experience required.
• Over 3 years in enterprise cybersecurity with direct exposure to AI/ML, MLOps, or cloud security.
• Hands-on work with GenAI models, Retrieval-Augmented Generation pipelines, and frameworks such as PyTorch or TensorFlow.
• Strong grounding in vulnerability management, system hardening (including SELinux), PKI based encryption, and identity and access management (RBAC, SSO).
• Familiarity with AWS and Azure cloud platforms and virtualization technologies such as VMware vSphere or Citrix for secure deployments.
• Knowledge of PCI DSS, FISMA FIPS standards, DIACAP, and RMF; ability to develop system security plans aligned with these standards.

Technologies

• PyTorch
• TensorFlow
• Retrieval-Augmented Generation (RAG)
• MITRE ATLAS
• NIST AI Risk Management Framework
• OWASP AI Security guidelines
• AWS, Azure, Google Cloud Platform
• Splunk, New Relic
• Cisco ISE, Cisco ASA
• IDS/IPS, VPNs
• VMware vSphere, Citrix

Certifications

• CISSP, CISM, or specialized AI security certifications are highly preferred

Education

Bachelor's degree is preferred

Experience

• AI Cybersecurity: 3 years (Required)
• AI Architecture and AI Governance: 3 years (Required)
• Cybersecurity Engineer: 9 years (Required)