Monitoring and strengthening the security posture of our AI/ML systems, APIs, and model-serving environments.
Building detection and monitoring capabilities to identify risks such as model misuse, prompt injection, data poisoning, and unauthorized model access.
Partnering with development, operations, and security teams to secure AI environments across their full lifecycle.
Automating security monitoring and remediation workflows for AI systems.
Evaluating and implementing AI security tools and model governance solutions.
Contributing to the development of AI-specific risk frameworks, controls, and policies.
Staying current on the evolving AI risk landscape and supporting security assessments and testing of LLMs and AI services.

Knowledge equivalent to completing a Bachelor's degree in Computer Science or a related field.
3 to 5 years of experience in cybersecurity, security engineering, or risk management.
Hands-on experience with machine learning systems, LLMs (Anthropic Claude, OpenAI, or open-source models), or AI/ML platforms such as SageMaker, Azure ML, or Vertex AI.
Familiarity with adversarial machine learning concepts and model risk is preferred.
Experience with security tools, monitoring platforms, or security automation frameworks.
Experience in application security, DevSecOps, or secure software development lifecycle (SDLC) is a plus.

CyberSecurity AI Engineer

Key skills