Principal Cybersecurity Architect – Generative AI Security

Job Description SummaryWe are seeking a Principal Cybersecurity Architect – Generative AI Security to lead the design, governance, and secure adoption of Generative AI (GenAI) technologies across the enterprise. This role will act as the primary security partner to the AI Foundry and AI platform teams, ensuring AI systems—including LLMs, agentic frameworks, and autonomous workflows—are designed with security, compliance, and resilience from the ground up. The ideal candidate will define security strategy, establish enterprise controls, and create reusable patterns for GenAI solutions. You will operate at the intersection of AI innovation and cybersecurity—enabling rapid adoption of GenAI while managing emerging risks such as prompt injection, data leakage, model manipulation, and autonomous agent misuse.Job DescriptionKey ResponsibilitiesGenAI Security Architecture & StrategyDefine and own the enterprise security architecture for Generative AI systems, including LLM-based applications, agentic AI, and AI platformsPartner with the AI Foundry to design secure GenAI platforms, tools, and workflowsEstablish architectural standards and guardrails for AI system design, deployment, and operationEnsure alignment with enterprise cybersecurity policies, regulatory requirements, and risk frameworksSecure-by-Design AI SystemsEmbed secure-by-design principles into AI pipelines, including model access, data ingestion, inference, and output handlingSupport Business Application Solutions Engagement (BASE) reviews and partner with the AI foundry to design secure GenAI systems.Conduct architecture reviews to identify risks across AI systems, including data exposure, model misuse, and integration vulnerabilitiesPublish Risk Assessment Reports that include threats and mitigating controls aligned to GEV policies and standardsDefine required security controls across the AI lifecycle (training, fine-tuning, inference, and retrieval-augmented workflows)AI Threat Modeling & Risk ManagementLead threat modeling and risk assessments for GenAI systems using frameworks such as:OWASP Top 10 for LLM ApplicationsOWASP Top 10 for Agentic ApplicationsMITRE ATT&CK / ATLAS (for AI threats)Identify threats including:Prompt injection and indirect prompt manipulationModel inversion and data exfiltrationAgent autonomy abuse and unsafe tool executionDefine mitigating controls and risk treatment strategiesZero Trust for AI & Agent SecurityApply Zero Trust principles to AI systems, including:Identity and authentication for AI agents and servicesLeast-privilege access to tools, APIs, and data sourcesContinuous validation of agent actions and interactionsDefine security models for agent-to-agent, agent-to-system, and agent-to-data interactionsImplement guardrails to constrain agent autonomy and enforce policy complianceModel Context Protocol & AI Integration SecurityDefine secure patterns for Model Context Protocol (MCP) and agent orchestration frameworksEnsure secure handling of context, memory, and tool invocation across AI workflowsEstablish governance for data access and context injection into LLMs and agentsEvaluate and secure integrations with internal APIs, SaaS platforms, and data servicesReusable AI Security Patterns & FrameworksCreate and publish enterprise-approved GenAI security patterns and reference architecturesStandardize controls for common GenAI use cases (chatbots, copilots, autonomous agents, RAG systems)Enable rapid adoption through reusable patterns that align to enterprise policiesGovernance, Policy & ComplianceEstablish enterprise policies, standards, and frameworks for AI security and governanceEnsure AI systems meet requirements for data privacy, compliance, and auditabilityPartner with GRC, Legal, and Risk teams to define AI governance modelsDevelop controls for monitoring, logging, and incident response for AI systemsTechnical Leadership & Enterprise InfluenceServe as the enterprise subject matter expert for GenAI security architectureInfluence AI strategy and adoption through security leadershipMentor architects and engineers on AI security best practicesRepresent the organization in AI security initiatives, vendor discussions, and standards bodiesRequired Qualifications8+ years of cybersecurity experience with strong focus on application, cloud, or AI security architectureHands-on experience securing Generative AI / LLM-based systemsKnowledge of:OWASP Top 10 for LLM ApplicationsOWASP Top 10 for Agentic ApplicationsStrong understanding of Zero Trust architecture, applied to AI and distributed systemsExperience with LiteLLM AI gateway and Prisma AIRSExperience with AI/ML platforms and LLM ecosystemsUnderstanding of threat modeling frameworks (MITRE ATT&CK, ATLAS, OWASP)Experience securing APIs, data pipelines, and microservices architecturesStrong ability to influence cross-functional teams and lead at an enterprise levelPreferred QualificationsExperience working with AI Foundries or enterprise AI platformsFamiliarity with M