Why This Role Stands Out
This hybrid role offers a unique opportunity to shape the security of cutting-edge AI cloud platforms, providing significant career growth in a highly sought-after field. You'll thrive here if you possess deep AWS and AI security expertise and enjoy building robust, automated security solutions. Apply now to become a key player in pioneering AI security within a reputable company.
Quick Overview
Job Description
Role: AI Cloud Security Engineer
Experience: 10+ Years
Note: Only on W2
Position Overview
The AI Cloud Security Engineer will implement and operationalize enterprise security capabilities across Airlines'' cloud-hosted AI platforms. This role is primarily responsible for establishing preventive, detective, and governance controls for Generative AI and Agentic AI workloads hosted on AWS, with an emphasis on AWS Bedrock Security Guardrails, CrowdStrike AIDR for Agents, and frontier model security.
The ideal candidate bridges architecture design and hands-on automation, integrating frameworks such as NIST AI RMF, OWASP Top 10 for LLM Applications, and MITRE ATLAS into enterprise CI/CD pipelines and cloud security operating models.
Required Skills & Experience (Prioritized)
1. AWS AI & Bedrock Security (5+ years Cloud, 1–2+ years AI Security): Direct hands-on experience configuring AWS Bedrock Guardrails, model access policies, content moderation filters, and foundation model protections.
2. AWS Cloud Engineering & IaC: Strong proficiency with AWS core security (IAM, SCPs, AWS Organizations) and Infrastructure as Code (Terraform or CloudFormation).
3. Runtime Protection & EDR/AIDR: Proven experience deploying and managing CrowdStrike Falcon, CrowdStrike AIDR, or equivalent cloud runtime detection platforms.
4. GenAI / LLM / Agentic AI Security: Deep technical understanding of RAG architectures, AI agent frameworks, prompt injection mitigations, output validation, and token abuse prevention.
5. AI Vulnerability Testing: Practical experience conducting security assessments and penetration tests specific to LLMs, tool integrations, and data leakage scenarios.
6. CI/CD & DevSecOps: Experience integrating automated security gates and policy-as-code into continuous integration/continuous deployment pipelines.
7. Cloud Logging & Observability: Expertise in aggregating AI telemetry via Amazon CloudWatch, SIEM tools, or OpenTelemetry.
Qualifications & Education
· Education: Bachelor’s degree in Cybersecurity, Computer Science, Information Systems, Data Science, Engineering, or equivalent practical experience. Advanced degree preferred.
· Basic Requirements: Must be at least 18 years old with legal authorization to work in the United States without sponsorship (Immigration Reform Act of 1986).
Preferred Certifications
· AWS Certified Security – Specialty
· AWS Certified AI Practitioner or AWS Cloud Practitioner
· CrowdStrike Falcon Platform Certifications (e.g., CCFA, CCFR)
· Industry Security Certifications: CISSP, CCSP, or GIAC Cloud Security (GCSA/GPCS)
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