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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:

Responsible for leading, developing and maintaining the technical IT/cyber security capabilities necessary for safeguarding the firm's information systems and the Cybersecurity Principal Engineer (AI Cloud Security) is part of Truist’s AI Security Engineering function and is responsible for designing, engineering, deploying, and operating security controls for AI, ML, and Generative AI systems across cloud platforms.

This role focuses on hands on engineering, enabling secure AI usage through cloud-native security controls, automation, and infrastructure as code, and operationalizing enterprise AI security standards. Engineers in this role work closely with AI platform teams, cloud engineering, governance, and risk partners to ensure AI systems are secure by design, compliant by default, and scalable across the enterprise.

ESSENTIAL DUTIES AND RESPONSIBILITIES

Essential Duties and Responsibilities

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

Lead 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.

Lead Infrastructure as Code & Automation

• Design and implement Infrastructure as Code (IaC) using Terraform and CloudFormation to deploy AI security controls consistently.

• Build and maintain CI/CD pipelines (GitLab) for security tooling, guardrails, and configuration‑as‑code.

• Automate operational workflows using Python and scripting to reduce manual security operations.

Lead 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).

Lead 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.

QUALIFICATIONS

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 and 10 years of experience in systems engineering or an equivalent combination of education and work experience

• Strong functional and technical knowledge of information/cyber security capabilities with deep expertise in one or more of the following areas: Encryption, Data Security, A