Principal AI Security Engineer

CDW

. Own CDW's AI security assessment program, including its process, criteria, and risk tiers for approving, restricting, monitoring, or blocking AI use cases, platforms, vendors, and shadow AI .

Posted 10/8/2026full-timeRemote • United StatesLead💰 $172,000 - $240,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI security assessment, including the design and implementation of security architectures, risk management, and compliance with security standards across AI systems. Proficient in securing AI technologies, managing identities, and leading cross-functional teams to enhance AI security practices.

Highest-signal resume keywords

AI Security AssessmentSecurity Architecture DesignProduction AI SecurityRisk ManagementIdentity and Access Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Security EngineeringAI/ML System SecurityLLM UnderstandingVulnerability DiscoveryAdversarial Testing

Soft Skills

Influencing Senior LeadersCross-Functional CollaborationMentoring Security Engineers

Tools & Technologies

Microsoft Copilot StudioAzure AI ServicesOpenAIMCP-Based IntegrationsAI Security Posture Management

Certifications & Qualifications

CISSPCCSPOSCP

Industry Keywords

Zero Trust PrinciplesAI GuardrailsAI ObservabilitySecurity OperationsDetection and Response

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformSDLC

About the role

Key responsibilities & impact

Own CDW's AI security assessment program, including its process, criteria, and risk tiers for approving, restricting, monitoring, or blocking AI use cases, platforms, vendors, and shadow AI
Lead security assessments of AI systems, agents, and integrations before and after deployment
Partner with the AI Council, AppSec, and platform teams to incorporate assessment findings into AI use case reviews
Evaluate third-party AI vendors, purchased AI capabilities, and unapproved AI use against CDW's AI security requirements and guardrails
Define methods and tools for AI red teaming, including automated adversarial testing
Assess AI-related controls across CDW's security stack, identify gaps, and drive root-cause remediation
Define and own enterprise AI security architecture, standards, reference architectures, and secure design patterns
Set security requirements across the AI lifecycle from data handling and model selection through deployment, monitoring, and retirement
Define trust boundaries, authorization models, and least privilege for single-agent and multi-agent systems
Design end-to-end security for LLM inference pipelines, AI agents, MCP-based tool orchestration, and agentic workflows
Design and deploy guardrails, sandboxes, runtime controls, and AI gateway capabilities
Build or implement governance for AI identities, including agents, service principals, workload identities, and delegated access
Partner with Identity Engineering, Detection Engineering, and Security Operations teams on identity standards, detections, telemetry, and response playbooks
Work with engineering, data science, product, and infrastructure teams to embed security from design through production
Present risk assessments, recommendations, and investment priorities to senior leadership and security governance bodies
Mentor security engineers and architects to grow AI security expertise across CDW

Requirements

What you’ll need

Bachelor's degree and 10+ years in security engineering or security architecture, including hands-on work securing AI/ML systems, or 14+ years of experience in security engineering or security architecture, including hands-on work securing AI/ML systems
Proven experience designing and leading security assessments of AI systems, platforms, or vendors, and turning findings into clear, risk-based decisions
Hands-on experience securing production AI technologies, including deploying AI guardrails or sandboxes, managing AI or agent identities, detecting or mitigating prompt injection, or implementing AI security tooling
Experience building or evaluating security for production AI systems, beyond research or theory
Solid understanding of LLMs, including pretraining, fine-tuning, RLHF, inference, retrieval-augmented generation, and safety alignment, and how each layer can be attacked
Experience securing AI platforms and agent frameworks such as Microsoft Copilot Studio, Azure AI services, OpenAI or Anthropic tool use, MCP-based integrations, Semantic Kernel, or LangChain
Experience securing AI deployments in public cloud (Azure, AWS, or GCP), identity and access management, and zero trust principles
Proven ability to influence senior leaders and cross-functional teams without direct authority
Experience on a security team defending production AI systems at scale, or at a frontier AI lab, a plus
Background in Infrastructure, Cloud, Platform, or Corporate Security, Security Operations, or Detection and Response, a plus
Software security review, secure SDLC, vulnerability discovery, or offensive security experience, a plus
Published work, conference talks, CTF results, or production red team work in prompt injection, jailbreak research, or adversarial ML, a plus
Experience with AI security posture management, AI gateways, or AI observability platforms, a plus
Relevant certifications such as CISSP, CCSP, OSCP, or AI security credentials, a plus

Benefits

Comp & perks

Annual bonus target of 15% subject to terms and conditions of plan
Benefits package detailed at https://cdw.benefit-info.com/
Salary ranges may be subject to geographic differentials