AI Security Engineer

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 cel