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MSI - (Marvell Semiconductor Inc.) US

AI Security Engineer

Santa Clara, CA, United States
Austin, TX, United States

$131,540 to $197,000 USD / year

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Job details

Pay: $131,540 to $197,000 USD / year
Experience: 5 to 8 years in cybersecurity engineering with hands-on experience deploying and operating enterprise security platforms
Posting language: English
Posted: Oct 30, 2026

Original job description

About Marvell Marvell’s semiconductor solutions are the essential building blocks of the data infrastructure that connects our world. Across enterprise, cloud and AI, and carrier architectures, our innovative technology is enabling new possibilities.

At Marvell, you can affect the arc of individual lives, lift the trajectory of entire industries, and fuel the transformative potential of tomorrow. For those looking to make their mark on purposeful and enduring innovation, above and beyond fleeting trends, Marvell is a place to thrive, learn, and lead.

Your Team, Your Impact

Marvell's AI footprint is expanding rapidly across the tools employees use, the systems we build, and the third-party software we depend on. This role ensures that expansion doesn't outpace our security controls: owning the platforms and technical capabilities that identify AI risk, enforce protection, and drive remediation across the enterprise.

This is a hands-on engineering role on the Cyber Engineering & Platform team, with cross-functional reach into IT, GRC, IAM, AppSec, and Security Architecture. The right person brings deep technical capability, sound risk judgment, and the ability to communicate clearly across engineering and business audiences. What You Can Expect

Administer and operate the AI security platform, designing and implementing preventive and detection policies that govern AI usage, enforce data protection controls, and surface risk across the environment
Serve as the cybersecurity representative across Marvell's AI platform ecosystem, partnering with GRC, Security Architecture, and enablement teams to define, validate, and enforce security requirements
Continuously assess AI assets for misconfigurations, excessive permissions, and policy gaps across SaaS, cloud, end user devices, and infrastructure where AI agents operate
Deploy and operate runtime protection capabilities, blocking prompt injection, data leakage, jailbreaks, and malicious content in real time
Partner with IAM, IT, and AppSec teams to enforce identity controls for human and agent identities, establish guardrails around autonomous AI agents, and validate AI model integrity prior to deployment
Leverage AI observability telemetry to identify anomalous behavior, policy violations, and emerging risk patterns and drive remediation with accountability across IT and business partners
Collaborate with Endpoint, Identity, SecOps, and other Cyber teams to ensure AI risk is visible and actionable across the existing security stack
Partner with Security Architecture to develop and maintain AI security standards, and support GRC as the engineering team's subject matter expert on AI risk
Track and report posture trends and risk reduction progress to security leadership and business stakeholders

What We're Looking For

5 to 8 years in cybersecurity engineering with hands-on experience deploying and operating enterprise security platforms
Demonstrated 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 core enterprise security platforms including EDR, SIEM, DLP, SOAR, and NGFW
Experience securing AI workloads across cloud platforms (GCP, AWS, Azure) and SaaS environments
Familiarity with AI platform components including LLM gateways, MCP frameworks, RAG architecture, and agentic workflow platforms
Understanding of identity and access management in AI contexts including agent identity, token management, RBAC, and SSO
Experience with leading LLM providers (Claude, ChatGPT, Gemini) and AI assisted coding tools (Cursor, Claude Code, 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 communicator, effective in both technical and executive or audit settings
Familiarity with AI risk frameworks including 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; Master's degree preferred.
Industry certifications in cyber security and cloud are a plus, including CISSP, CAISP, CCSP, cloud platform security specializations (AWS, GCP, Azure) or equivalent GAIC

Expected Base Pay Range (USD) 131,540 - 197,000, $ per annum The successful candidate’s starting base pay will be determined based on job-related skills, experience, qualifications, work location and market conditions. The expected base pay range for this role may be modified based on market conditions.

This role is eligible to participate in Marvell's bonus and equity plans, including a new hire equity grant and annual equity refreshers, ensuring you are rewarded for your contributions and remain invested in the company's long-term success. Additional Compensation and Benefit Elements Marvell is committed to providing exceptional, comprehensive benefits that support our employees at every stage - from internship to retirement and through life’s most important moments. Our offerings are built around four key pillars: financial well-being, family support, mental and physical health, and recognition. Highlights include an employee stock purchase plan with a 2-year look back, family support programs to help balance work and home life, robust mental health resources to prioritize emotional well-being, and a recognition and service awards to celebrate contributions and milestones. We look forward to sharing more with you during the interview process. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status.

Any applicant who requires a reasonable accommodation during the selection process should contact Marvell HR Helpdesk at TAOps@marvell.com.

Interview Integrity To support fair and authentic hiring practices, candidates are not permitted to use AI tools (such as transcription apps, real-time answer generators like ChatGPT or Copilot, or automated note-taking bots) during interviews.

These tools must not be used to record, assist with, or enhance responses in any way. Our interviews are designed to evaluate your individual experience, thought process, and communication skills in real time. Use of AI tools without prior instruction from the interviewer will result in disqualification from the hiring process.

This position may require access to technology and/or software subject to U.S. export control laws and regulations, including the Export Administration Regulations (EAR). As such, applicants must be eligible to access export-controlled information as defined under applicable law. Marvell may be required to obtain export licensing approval from the U.S. Department of Commerce and/or the U.S. Department of State. Except for U.S. citizens, lawful permanent residents, or protected individuals as defined by 8 U.S.C. 1324b(a)(3), all applicants may be subject to an export license review process prior to employment.

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More about this job

Skills

Data protection
Cybersecurity
Security regulations
Identity and access management
Leadership
ML
Supply chain management
Google Cloud
AWS
Microsoft Azure
Workflow
GitHub
Machine learning
Computer science
Computer technology
CISSP
Communication skills

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