AI Security Engineer

Marvell Technology

. Administer and operate the AI security platform .

Posted 10/30/2026full-timeUnited StatesMid-LevelSenior💰 $131,540 - $197,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in administering AI security platforms and implementing security policies for AI usage and data protection. Proficient in assessing AI assets, enforcing identity controls, and collaborating with cross-functional teams to mitigate risks in AI environments.

Highest-signal resume keywords

Cybersecurity EngineeringAI Security PlatformsRisk AssessmentIdentity Access ManagementTechnical Security Standards

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Cybersecurity EngineeringAI Risk DomainsAI Security PlatformsData ExposurePrompt InjectionSupply Chain RiskModel IntegrityDetection EngineeringPolicy as CodeData Governance

Soft Skills

Strong Communication SkillsInfluencing Remediation Outcomes

Tools & Technologies

Palo Alto Prisma AIRSCisco AI DefenseProtect AILakeraWiz AI SecurityEDRSIEMDLPSOARNGFW

Certifications & Qualifications

CISSPCAISPCCSPAWS Security SpecializationGCP Security SpecializationAzure Security Specialization

Industry Keywords

NIST AI RMFMITRE ATLASOWASP LLM Top 10SemiconductorHardwareHigh IP TechnologyAI Red TeamingAdversarial Machine Learning

Tech Stack

Tools & technologies

AWSAzureCloudCyber SecurityGoogle Cloud Platform

About the role

Key responsibilities & impact

Administer and operate the AI security platform
Design and implement preventive and detection policies governing AI usage and data protection
Serve as the cybersecurity representative across Marvell's AI platform ecosystem
Partner with GRC, Security Architecture, and enablement teams to define, validate, and enforce security requirements
Assess AI assets for misconfigurations, excessive permissions, and policy gaps across SaaS, cloud, end-user devices, and infrastructure
Deploy and operate runtime protection capabilities against prompt injection, data leakage, jailbreaks, and malicious content
Partner with IAM, IT, and AppSec teams to enforce identity controls and guardrails for autonomous AI agents
Validate AI model integrity before deployment
Use AI observability telemetry to identify anomalous behavior, policy violations, and emerging risk patterns
Drive remediation with IT and business partners
Collaborate with Endpoint, Identity, SecOps, and Cyber teams to integrate AI risk into the security stack
Develop and maintain AI security standards with Security Architecture
Support GRC as the engineering subject matter expert on AI risk
Track and report posture trends and risk reduction progress to security leadership and business stakeholders

Requirements

What you’ll need

5 to 8 years in cybersecurity engineering with hands-on experience deploying and operating enterprise security platforms
Experience with AI and ML risk domains including data exposure, shadow AI, prompt injection, supply chain risk, and model integrity
Hands-on experience with AI security platforms such as Palo Alto Prisma AIRS, Cisco AI Defense, Protect AI, Lakera, or Wiz AI Security
Familiarity with EDR, SIEM, DLP, SOAR, and NGFW
Experience securing AI workloads across GCP, AWS, Azure, and SaaS environments
Familiarity with LLM gateways, MCP frameworks, RAG architecture, and agentic workflow platforms
Understanding of agent identity, token management, RBAC, and SSO
Experience with Claude, ChatGPT, Gemini, Cursor, Claude Code, and GitHub Copilot
Experience contributing to or owning technical security standards or control frameworks
Proven ability to influence remediation outcomes across IT and business teams without direct authority
Strong communication skills in technical and executive or audit settings
Familiarity with NIST AI RMF, MITRE ATLAS, or OWASP LLM Top 10
Experience in semiconductor, hardware, or high IP technology environments
Background in detection engineering, security architecture, or security operations applied to AI contexts
Exposure to AI red teaming methodologies or adversarial machine learning concepts
Familiarity with policy as code concepts and data governance tooling in AI environments
Bachelor's degree in Computer Science, Information Technology, Cybersecurity, or related field
Eligibility to access export-controlled information under U.S. law; applicants may be subject to export license review
Industry certifications in cybersecurity and cloud are a plus, including CISSP, CAISP, CCSP, AWS/GCP/Azure security specializations, or equivalent GAIC

Benefits

Comp & perks

Bonus and equity plans
New hire equity grant
Annual equity refreshers
Employee stock purchase plan with a 2-year look back
Family support programs
Mental health resources
Recognition and service awards