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Principal AI Security Engineer

Cerebras· IT & Security
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United States and CanadaFull-timePosted 3mo ago

About the role

Lead hands-on security engineering for enterprise IT, infrastructure, AI platforms, and agentic systems. Design and build security controls for systems that support training, inference, model serving, customer workloads, internal automation, and AI-assisted development across product, cloud, infrastructure, identity, runtime, data, and developer platforms.

Responsibilities

  • Define security architecture and build controls for AI platforms, training and inference workflows, model-serving systems, customer workloads, developer workflows, and agentic security patterns.
  • Develop reusable AI and agent security patterns for identity, authorization, delegated authority, scoped tool access, MCPs, connectors, secrets, approvals, isolation, auditability, and policy enforcement.
  • 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.
  • Automate security reviews, policy checks, evidence collection, control validation, and remediation.
  • Instrument AI, agent, and platform activity with telemetry, traceability, policy decisions, audit logs, anomaly signals, and response workflows.
  • Lead hands-on security reviews and influence product, platform, infrastructure, and security architecture through practical design changes and reusable controls.

Qualifications

  • 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 programming language
  • Experience designing, building, operating, and improving security controls as code
  • 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.
  • 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.

Skills

Required:Security architecture designInfrastructure as codeCloud security (AWS)Identity and access managementRuntime security (containers/Kubernetes)
Nice to have:AI security / agentic security

Benefits

  • Not specified in description
Last updated Aug 30, 2026. Interested? Apply on the company site.

About Cerebras

Cerebras is the go-to platform for fast and effortless AI training. Learn more at cerebras.ai.

Cerebras is the go-to platform for fast and effortless AI training.

AICerebras Wafer-Scale Enginechipshardwareinferenceliquid-ai-recruiting-targetmultimodalsetter-30
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