AI Security Architect

This role will focus on protecting AI/ML models, data pipelines, and GenAI applications from emerging threats while enabling safe innovation.Key ResponsibilitiesDesign secure architectures for AI/ML systems, including model training, inference, and deployment pipelinesDefine security controls for LLMs (Large Language Models), GenAI platforms, and AI APIsEmbed security into MLOps pipelines (DevSecOps for AI)Conduct threat modeling for AI systems (e.g., prompt injection, model poisoning, data leakage)Develop risk frameworks aligned with NIST AI Risk Management FrameworkIdentify and mitigate adversarial AI threats and abuse casesEnsure protection of training and inference data (PII, PHI, proprietary data)Implement data governance, anonymization, and encryption strategiesEnsure compliance with regulations (GDPR, HIPAA, etc.)Secure AI workloads across cloud platforms such as Amazon Web Service, Microsoft Azure, Google Cloud, IBM CloudArchitect secure integrations with AI services and APIsProtect

against model theft, inversion, and extraction attacksImplement model monitoring for drift, anomalies, and abuseEnsure secure model storage, versioning, and access controlEstablish AI security policies, standards, and guardrailsAlign with industry AI frameworks such as ISO AI standards (e.g., ISO/IEC 42001)Support audit, regulatory, and CIO and CISO reportingPartner with data scientists, ML engineers, and product teamsProvide security guidance for AI product developmentLead security reviews and architecture boardsMentor security engineers on AI-specific threatsRequired QualificationsBachelor’s or Master’s degree in Computer Science, Cybersecurity, or related field8+ years in cybersecurity architecture or engineeringExperience securing AI/ML systems or data platformsStrong understanding of cloud security (IAM, network, containers, serverless), API security and microservices, encryption, key management, and identity systemsDevelopment of Agent and Agentic AI for security use casesExperience with MCPPreferred QualificationsExperience with LLMs (e.g., prompt engineering, RAG architectures)Familiarity with adversarial ML techniquesKnowledge of tools like MLflow, Kubeflow, SageMaker, SIEM/XDR platformsCertifications: CISSP, CCSP, or cloud security certificationsExperience in semiconductor industry is a plusKey SkillsAI Threat Modeling (Prompt Injection, Data Poisoning, Model Evasion)Secure MLOps / DevSecOpsZero Trust ArchitectureData Privacy & GovernanceCloud-Native SecurityRisk & Compliance ManagementThe annual salary range for California is $164,500 to $305,500. You may also be eligible to receive incentive compensation: bonus, equity, and benefits.

Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the salary range is a guideline and compensation may vary based on factors such as qualifications, skill level, competencies and work location. Our benefits programs include: paid vacation and paid holidays, 401(k) plan with employer match, employee stock purchase plan, a variety of medical, dental and vision plan options, and more.We’re doing work that matters. Help us solve what others can’t.