Cerebras Systems
Principal AI Security Engineer
US and Canada Offices · Principal
Sponsorship not specifiedDetected 28 days ago
PythonAWSKubernetesCI/CDOAuthMachine LearningLLMsComplianceCommunication
About the role
- You will work across product, cloud, infrastructure, identity, runtime, data, and developer platforms to protect sensitive data, enterprise and customer environments, models, tools, agents, and control planes.
- This is a principal IC role for someone who can turn ambiguous AI and platform security risks into practical architecture, reusable controls, and production-ready systems that teams can adopt by default.
Responsibilities
- 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, auditability, and
- 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.
- Lead hands-on security reviews and influence product, platform, infrastructure, and security architecture through practical design changes and reusable controls.
Requirements
- 10+ years of experience in security engineering, platform security, infrastructure security, product security, or related technical security roles.
- Practical experience securing runtime environments such as containers, Kubernetes, isolated workloads, secure development environments, distributed compute platforms, or production service infrastructure.
- Familiarity with AI security, LLM application security, agentic workflows, MCPs, prompt injection, autonomous coding agents, or AI platform security.
- Ability to reason about cross-system risk involving identity, data, models, tools, networks, workflows, approvals, and automation.
- Strong written communication skills and the ability to influence senior technical stakeholders across Security, Product, IT, Infrastructure, and Engineering.
- 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.
Skills
- Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups.
- AI, ML, training, inference, model-serving, or large-scale compute
- Coding agents, agent platforms, MCP servers, internal developer platforms, or AI-assisted development environments.
- Workload identity, secrets brokers, token brokers, short-lived credentials, privileged access, or zero-standing-privilege architectures.
- Policy-as-code, authorization services, runtime enforcement layers, or security control
- Detection, investigation, and response workflows for cloud, infrastructure, identity, AI, or agent
Company info
- Build a breakthrough AI platform beyond the constraints of the GPU.
- Publish and open source their cutting-edge AI research.
- Work on one of the fastest AI supercomputers in the world.
- Enjoy job stability with startup vitality.
- Our simple, non-corporate work culture that respects individual beliefs.
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This listing is sourced directly from Cerebras Systems's careers page and normalized into a canonical job model.