Principal AI Security Engineer

Cerebras

. Lead hands-on security engineering for enterprise IT, infrastructure, AI platforms, and agentic systems .

Posted 11/6/2026full-timeSunnyvale • California • United StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive expertise in security engineering, particularly in designing and implementing security controls for AI platforms and infrastructure. Proficient in Python and cloud security, with a strong focus on identity and access management, automated policy validation, and secure software delivery.

Highest-signal resume keywords

Security EngineeringPython ProgrammingCloud Security (AWS)Identity And Access ManagementAI Security

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Security Controls As CodeInfrastructure As CodePolicy As CodeAutomated ValidationRuntime Environment SecurityKubernetes SecuritySecrets ManagementMFAOAuthLeast Privilege

Soft Skills

Strong Written CommunicationInfluencing Stakeholders

Tools & Technologies

GitOpsCI/CDTelemetryAudit LogsAnomaly Detection

Certifications & Qualifications

U.S. Export Compliance Assessment

Industry Keywords

AI SecurityAgentic WorkflowsModel ServingWorkload IdentityPolicy-As-Code

Tech Stack

Tools & technologies

AWSCloudKubernetesPython

About the role

Key responsibilities & impact

Lead hands-on security engineering for enterprise IT, infrastructure, AI platforms, and agentic systems
Design and build security controls for training and inference workflows, model-serving systems, customer workloads, 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 and tool interaction, and blast radius
Build security capabilities 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
Turn emerging AI and agent risks into reusable architecture, safer identity and authorization models, scoped tool access, runtime containment, secure software delivery, automated policy validation, telemetry, and default-adoptable controls

Requirements

What you’ll need

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 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 ability to influence senior technical stakeholders
Experience in several relevant areas, including AI/ML, training, inference, model serving, large-scale compute, coding agents, MCP servers, workload identity, secrets brokers, policy-as-code, authorization services, runtime enforcement, software delivery security, detection, investigation, and response workflows
Must complete the U.S. export compliance citizenship/permanent residency assessment

Benefits

Comp & perks

Publish and open source cutting-edge AI research
Work on one of the fastest AI supercomputers in the world
Job stability with startup vitality
Simple, non-corporate work culture that respects individual beliefs
Continuous learning, growth and support
Equal and diverse work environment