AI Security Engineer

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

You design, build, and run security controls for artificial intelligence systems across the full lifecycle. You secure model development, training data, pipelines, APIs, and AI-enabled applications. You work with product, engineering, data science, and compliance teams to reduce exposure from model misuse, data leakage, supply chain threats, and adversarial attacks. You deliver measurable improvements in AI governance, detection, and incident response.

Required Qualifications

• Bachelor’s degree in Cybersecurity, Artificial Intelligence, Computer Science, or related highly technical field
• 5+ years in security engineering, application security, cloud security, or detection engineering
• Experience securing LLM-based applications, RAG systems, or agentic workflows
• Familiarity with adversarial ML concepts, such as prompt injection, model inversion, and model extraction
• Experience with one or more cloud platforms, AWS, Azure, or GCP
• Experience with Kubernetes and container security
• Hands‑on experience with at least one programming language, Python preferred
• Strong understanding of AI, LLMs, API security, identity, secrets management, and cloud controls
• Experience building security controls into CI and CD pipelines
• Proven ability to lead cross‑functional security work with engineering and product teams
• Effectively communicate complex technical concepts to both technical and non‑technical stakeholders
• Effectively communicate to leadership and know when to elevate with proactive, clear, data‑driven insight, highlighting risks, roadblocks, and solutions
• Proven leadership capabilities with the ability to influence and drive change

Preferred Qualifications

• Master’s degree in Cybersecurity, Artificial Intelligence, Computer Science, or related highly technical field
• AI/ML certifications (e.g., Microsoft Azure AI Engineer, AWS ML Specialty, GIAC Machine Learning Engineer, ISC2 Building AI Strategy)
• Experience with security telemetry and detections in SIEM or EDR platforms