Principal AI Security Engineer

Security Architecture:

• Define security architecture and build controls for AI platforms, training, inference, model-serving, and agentic systems.
• Develop reusable AI and agent security patterns for identity, authorization, delegated authority, and scoped tool access.
• Design runtime controls that constrain execution, access, data exposure, and blast radius.

Automation and Tools:

• Build security capabilities as code using IaC, CI/CD, GitOps, and automated validation.
• Automate security reviews, policy checks, evidence collection, and control validation.
• Instrument AI, agent, and platform activity with telemetry, traceability, and audit logs.

Collaboration and Influence:

• Lead hands-on security reviews and influence product, platform, and infrastructure architecture.
• Work across product, cloud, infrastructure, identity, and developer platforms to protect sensitive data and environments.
• Shape how Cerebras secures AI training, inference, and customer workloads with reusable controls.