Senior AI Security Engineer

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Regular or Temporary:
Regular

Language Fluency: English (Required)

Work Shift:
1st shift (United States of America)


Please review the following job description:

*** This role is 5 days a week in the Atlanta or Charlotte Office**
* The Senior AI Security Engineer helps design, implement, test, and operate the controls that keep enterprise AI systems safe, governed, and production ready.

This role focuses on the security engineering foundations required for AI-enabled applications, agents, prompt-driven workflows, and tool-integrated automations operating in a regulated enterprise environment.

This is a hands-on engineering role within the Forge AI Security & Governance model.

The engineer supports guardrail implementation, prompt-injection defense, output filtering, monitoring, secure tool-use boundaries, logging, detection content, and deployment-readiness controls for AI-enabled systems.

The work spans design, testing, automation, detection engineering, and operational support across the AI delivery lifecycle.

Daily work includes implementing security controls for AI and agentic systems, validating configurations, supporting adversarial test preparation, building monitoring logic, partnering with engineering to harden prompt and tool behaviors, documenting controls, and ensuring AI solutions meet enterprise safety, traceability, and governance requirements before and after deployment.

ESSENTIAL DUTIES AND RESPONSIBILITIES

Following is a summary of the essential functions for this role. Other duties may be assigned as needed.

AI & Cloud Security Engineering

• Engineer and deploy security controls for AI/ML and Generative AI systems, including model-level, data-level, and platform-level protections.
• Implement AI guardrails and safety controls (e.g., prompt injection defenses, content safety filters, policy enforcement, model access controls).
• Support secure AI platform onboarding for internal teams, ensuring alignment with Truist AI Security Standards and Review Processes.
• Perform technical security assessments of AI systems and cloud-hosted AI services.

Infrastructure as Code & Automation

• Design and implement Infrastructure as Code (IaC) using Terraform and Cloud Formation to deploy AI security controls consistently.
• Build and maintain CI/CD pipelines (Git Lab) for security tooling, guardrails, and configuration-as-code.
• Automate operational workflows using Python and scripting to reduce manual security operations.

Cloud Platform Security

• Engineer secure, scalable cloud environments supporting AI workloads across AWS and Azure.
• Implement and integrate cloud security tooling (e.g., Wiz) to provide visibility and control over AI assets.
• Secure containerized and orchestrated workloads supporting AI pipelines (ECS, EKS, Kubernetes).

Collaboration & Enablement

• Partner with AI platform teams, application engineers, cloud security, and governance stakeholders to embed security into AI delivery.
• Contribute to the evolution of enterprise AI security standards, patterns, and reference architectures.
• Support incident response, threat modeling, and remediation activities related to AI systems.

Required Qualifications
The requirements listed below are representative of the knowledge, skill and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• Bachelor's degree or equivalent education, training, and work-related experience.
• Minimum of 7 years of experience in security engineering or related cybersecurity roles.
• Deep specialized knowledge in cybersecurity principles, theories, and concepts.
• P…