Cerebras

4 weeks ago

Principal AI Security Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Job Summary

Lead hands-on security engineering across enterprise IT, infrastructure, AI platforms, and agentic systems. Design and build security controls for training, inference, model serving, customer workloads, identity, runtime, data, and developer workflows—turning ambiguous AI risks into reusable, production-ready architectures. Build security capabilities as code (IaC, policy as code, GitOps, CI/CD), automate reviews and evidence collection, and instrument telemetry, audit logs, and response workflows to protect sensitive environments and control planes.

Location: United States, Canada

Workplace: Onsite

Employment Type: Full time

Job Function: Cybersecurity

Seniority: Sr. Manager level

Key Responsibilities

•Define security architecture and build controls for AI platforms, training/inference workflows, model-serving systems, customer/developer workflows, and agentic systems.
•Develop reusable AI and agent security patterns for identity, authorization, delegated authority, scoped tool access, MCPs, connectors, secrets, approvals, isolation, and auditability.
•Design runtime controls that constrain execution, access, data exposure, model/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.
•Automate security reviews, policy checks, evidence collection, control validation/remediation, and instrument telemetry, traceability, audit logs, anomaly signals, and response workflows.

Key Requirements

•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/tooling.
•Experience designing, building, operating, and improving security controls for AI platforms, training/inference workflows, or related production systems.
•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 (SSO, MFA, OAuth, service accounts, workload identity, authorization, privileged access, least privilege) and runtime security (containers, Kubernetes, isolated workloads).

Experience:10+ yearsPlatform securityCloud securityInfrastructure securityProduct securityAI security

Skills:Written communicationStakeholder influenceRisk reasoningHands-on engineering

Tech Stack:PythonAWSIAMSSOMFAOAuthKubernetesContainersGitOpsCI/CDInfrastructure as codeConfiguration as codePolicy as codeTelemetryAudit logs

Company Brief

Cerebras

Designs and builds wafer-scale AI accelerators and systems for large-scale deep learning workloads, delivering specialized hardware and software to accelerate model training and inference for enterprises and research institutions.

Industry: Hardware Devices

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Headquarters: Sunnyvale, United States

Founded: 2016

Website LinkedIn

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Cerebras

4 weeks ago

Principal AI Security Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Job Summary

Location: United States, Canada

Workplace: Onsite

Employment Type: Full time

Job Function: Cybersecurity

Seniority: Sr. Manager level

Key Responsibilities

•Define security architecture and build controls for AI platforms, training/inference workflows, model-serving systems, customer/developer workflows, and agentic systems.
•Develop reusable AI and agent security patterns for identity, authorization, delegated authority, scoped tool access, MCPs, connectors, secrets, approvals, isolation, and auditability.
•Design runtime controls that constrain execution, access, data exposure, model/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.
•Automate security reviews, policy checks, evidence collection, control validation/remediation, and instrument telemetry, traceability, audit logs, anomaly signals, and response workflows.

Key Requirements

•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/tooling.
•Experience designing, building, operating, and improving security controls for AI platforms, training/inference workflows, or related production systems.
•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 (SSO, MFA, OAuth, service accounts, workload identity, authorization, privileged access, least privilege) and runtime security (containers, Kubernetes, isolated workloads).

Experience:10+ yearsPlatform securityCloud securityInfrastructure securityProduct securityAI security

Skills:Written communicationStakeholder influenceRisk reasoningHands-on engineering

Tech Stack:PythonAWSIAMSSOMFAOAuthKubernetesContainersGitOpsCI/CDInfrastructure as codeConfiguration as codePolicy as codeTelemetryAudit logs

Company Brief

Cerebras

Industry: Hardware Devices

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Headquarters: Sunnyvale, United States

Founded: 2016

Website LinkedIn