AI Security Engineer: LLM & Cloud Security Leader

CBTS; Irving (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

CBTS in Irving, TX designs, builds, and runs security controls for AI systems across the full lifecycle. You secure model development, data, pipelines, APIs, and AI-enabled apps, collaborating with product, engineering, data science, and compliance teams to reduce model misuse and data leakage.

The role emphasizes governance, detection, and incident response, requiring deep expertise in AI/LLM security, cloud platforms, Kubernetes, and secure CI/CD pipelines.

Qualifications

• Bachelor’s degree in Cybersecurity, AI, CS or related field.
• 5+ years in security engineering, app security, cloud security, or detection engineering.
• Experience securing LLM-based apps, RAG systems, or agentic workflows.
• Familiarity with adversarial ML concepts (prompt injection, model inversion, extraction).
• Experience with AWS/Azure/GCP cloud platforms and Kubernetes.
• Hands-on with Python; strong understanding of AI/LLMs, API security, identity and cloud controls.
• Experience integrating security into CI/CD pipelines; ability to lead cross-functional security work.

Responsibilities

• Design, build, and run security controls across AI system lifecycles.
• Collaborate with product, engineering, data science, and compliance teams.
• Reduce exposure from model misuse, data leakage, and adversarial attacks.
• Deliver measurable improvements in AI governance, detection, and incident response.
• Communicate risks and security posture to leadership with data-driven insights.

Skills

Security engineering

Cross-functional collaboration

Cloud security

CI/CD security

Python programming

AI/LLM security

Leadership

Effective communication

Education

Bachelor’s degree in Cybersecurity/ CS

Master’s degree (preferred)

Tools

Kubernetes

Cloud platforms (AWS/Azure/GCP)

SIEM/EDR

Job description

CBTS in Irving, TX designs, builds, and runs security controls for AI systems across the full lifecycle. You secure model development, data, pipelines, APIs, and AI-enabled apps, collaborating with product, engineering, data science, and compliance teams to reduce model misuse and data leakage.

The role emphasizes governance, detection, and incident response, requiring deep expertise in AI/LLM security, cloud platforms, Kubernetes, and secure CI/CD pipelines.