AI Security Engineer

About the role

As an AI Security Engineer you will work at the intersection of cybersecurity, artificial intelligence, data and biotechnology. You will design, build and automate security controls that enable Amgen teams to develop and deploy AI safely at enterprise scale.

Key responsibilities

• Design and implement AI security controls for AI/ML applications, platforms, models, APIs, agents and supporting infrastructure.
• Deploy security tooling and automation on AWS, integrating AI security testing into engineering workflows.
• Integrate security into MLOps, LLMOps, DevSecOps and CI/CD pipelines for automated validation.
• Threat‑model AI systems and translate risks into practical engineering mitigations.
• Secure generative AI, large language models, vector databases and agentic workflows.
• Implement infrastructure and security controls as code using Terraform or similar IaC tools.
• Partner with AI and platform engineering teams to investigate threats and drive remediation.

Required profile

• Bachelor’s or Master’s degree in Computer Science, Cybersecurity, Engineering, IT or equivalent experience.
• 5+ years of hands‑on experience in cybersecurity, security engineering or cloud security.
• Strong programming or scripting ability to build security tooling and automation.
• Hands‑on experience with cloud‑native technologies, preferably AWS.
• Understanding of the AI/ML lifecycle, MLOps/LLMOps and security risks of generative AI.

Required skills

• AWS cloud services and APIs.
• Infrastructure‑as‑code tools such as Terraform.
• Container technologies like Docker and Kubernetes.
• Threat modeling and security testing methodologies.
• AI/ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face, LangChain).
• MLOps platforms (e.g., MLflow, SageMaker).
• Familiarity with security frameworks such as OWASP LLM, MITRE ATLAS and NIST AI Risk Management.