AI Security Engineer
About The Position
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. 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.
Requirements
- 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
- 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
Nice To Haves
- 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
Responsibilities
- 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
Benefits
- 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
- recognition and service awards to celebrate contributions and milestones
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What This Job Offers
Job Type
Full-time
Career Level
Senior
