AI Security Engineer

Marvell Technology•Austin, CA

4d•$131,540 - $197,000

About The Position

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.

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
Industry certifications in cyber security and cloud are a plus, including CISSP, CAISP, CCSP, cloud platform security specializations (AWS, GCP, Azure) or equivalent GAIC

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