Principal AI Security Engineer

Job summary

Responsibilities

Cerebras is seeking a Principal AI Security Engineer to lead hands-on security engineering for enterprise IT, infrastructure, AI platforms, and agentic systems.

• Define security architecture and build controls for AI platforms, training and inference workflows, model-serving systems, customer workloads, developer workflows, and agentic
• Develop reusable AI and agent security patterns for identity, authorization, delegated authority, scoped tool access, MCPs, connectors, secrets, approvals, isolation…
• Design runtime controls that constrain execution, access, data exposure, model and tool interaction, and blast radius.
• Build security capabilities as code using infrastructure as code, configuration as code, policy as code, GitOps, CI/CD, and automated validation.
• Define secure development patterns for AI systems, agents, prompts, tools, models, policies, evaluations, releases, and rollback.

What they're looking for

• 10+ years of experience in security engineering, platform security, infrastructure security, product security, or related technical security roles.
• Strong hands-on engineering ability in Python and at least one additional production
• Experience designing, building, operating, and improving security controls as
• Strong cloud and infrastructure security experience, preferably with AWS, including IAM, networking, secrets management, logging, and cloud-native control planes.
• Deep understanding of identity and access systems, including SSO, MFA, OAuth, service accounts, workload identity, authorization, privileged access, and least privilege.

Tech stack

• Python
• AWS
• Kubernetes