Generative AI Security Engineer — Hybrid/Remote

SMBC; Charlotte (NC); Hybrid; USD 140,000 - 170,000; Full time

Job summary

SMBC is seeking an AI Security Engineer to help secure the organization’s AI, machine learning, generative AI, and agentic AI platforms. You will collaborate with security, cloud, engineering, data, and risk teams to implement security controls across the AI lifecycle.

The role focuses on reducing AI-specific risks while enabling safe adoption of AI technologies enterprise-wide, with a hybrid work model and potential office-based days in Charlotte, NC.

Qualifications

• 3 to 5 years of experience in cybersecurity, security engineering, cloud security, or security architecture.
• Knowledge of enterprise security concepts, including networking, operating systems, web applications, IAM, authentication, privileged access controls, and certificate management.
• Understanding of application security, API security, modern threat techniques, and cloud security risks.

Responsibilities

• Design, implement, and maintain security controls for generative AI, LLMs, AI agents, and ML platforms.
• Develop secure architecture patterns, standards, and guardrails for AI solutions across data ingestion, model development, deployment, and inference workflows.
• Integrate AI security requirements into software development, DevSecOps, and MLOps processes.
• Secure AI platforms and services, including Azure AI, Azure OpenAI, AWS Bedrock, Databricks AI, and related cloud-native technologies.
• Monitor AI environments by implementing logging, telemetry collection, threat detection, and security monitoring capabilities.
• Assess AI solutions for risks such as prompt injection, model poisoning, data leakage, adversarial attacks, unauthorized access, insecure agent behavior, retrieval-augmented generation vulnerabilities, and supply chain threats.
• Partner with architecture, engineering, data science, privacy, legal, compliance, and cloud teams to incorporate security requirements into solution design, deployment, and operations.
• Support AI security testing, red team exercises, incident response preparedness, control validation, and continuous improvement initiatives.

Skills

Cybersecurity experience

Cloud security

AI security

Education

Bachelor’s degree in Information Security, Computer Science, Engineering

Tools

Azure

AWS

GCP

Job description

SMBC is seeking an AI Security Engineer to help secure the organization’s AI, machine learning, generative AI, and agentic AI platforms. You will collaborate with security, cloud, engineering, data, and risk teams to implement security controls across the AI lifecycle.

The role focuses on reducing AI-specific risks while enabling safe adoption of AI technologies enterprise-wide, with a hybrid work model and potential office-based days in Charlotte, NC.