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Enterprise AI Security Advisor
Eli Lilly and Company. Establish and own a companywide approach to securing AI agents, models, applications, and supporting infrastructure .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in AI security, including the establishment of security controls, risk assessment, and incident response for AI systems. Proficient in integrating security requirements into architecture and leading cross-functional teams in the development of AI security strategies.
Highest-signal resume keywords
AI Security Strategy DevelopmentCloud Security ExpertiseIncident Response Playbook CreationTechnical Leadership in CybersecurityExperience with OWASP Top 10 for LLM Applications
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Python ProgrammingAI Applications SecuritySecurity Architecture DesignData ProtectionIdentity and Access ManagementInference-Time GuardrailsAdversarial Red-TeamingAI Detection and Response ToolingModel Misuse PreventionSecurity Operations
Soft Skills
MentoringCollaborationInfluencing Executive DecisionsTechnical Direction SettingCommunication
Tools & Technologies
AWSAzureSIEMSOAREDRREST APIsInfrastructure-as-CodeAI GatewaysDLP for AI TrafficAgent Frameworks
Certifications & Qualifications
CISSPCCSPCloud Security Certifications
Industry Keywords
AI Governance FrameworksRegulated IndustriesHigh-Risk AI ClassificationsAuditability RequirementsMITRE ATLAS
Tech Stack
Tools & technologiesAWSAzureCloudCyber SecurityPython
About the role
Key responsibilities & impact- Establish and own a companywide approach to securing AI agents, models, applications, and supporting infrastructure
- Maintain a prioritized view of AI security risk and set priorities for teams and partners
- Own the roadmap for AI security controls, tooling, and improvements; report progress and measurable outcomes to leadership
- Advise senior leaders on emerging AI threats, safety-productivity trade-offs, and investment priorities
- Define security requirements and approved patterns for AI systems, including identity, permissions, data access, human approval, logging, monitoring, and incident response
- Publish reference architectures and acceptance criteria for AI applications, agents, and integrations
- Set control expectations for inference-time guardrails, AI gateways, and model and agent registries
- Integrate AI security requirements into security architecture review, risk acceptance, and change management processes
- Assess internally built AI systems and third-party AI products
- Develop and lead testing for prompt injection, sensitive data exposure, excessive permissions, unsafe agent actions, jailbreaks, and misuse scenarios
- Define evidence required before controls move from monitoring to blocking
- Maintain threat models using OWASP Top 10 for LLM Applications and MITRE ATLAS
- Evaluate, select, and tune security capabilities from cloud, endpoint, identity, data protection, and AI-specific platforms and vendors
- Establish visibility into enterprise AI usage and agent activity
- Lead the design and operation of AI guardrail services, including detection content, policy tuning, telemetry, dashboards, and integrations with SIEM, SOAR, EDR, identity, and ticketing platforms
- Define detection, alerting, and incident response playbooks for AI-specific events
- Partner with AI application and agent teams to incorporate security into design, build, and deployment
- Collaborate with privacy, legal, compliance, quality, and AI governance functions
- Mentor engineers and security operations personnel
- Engage vendors, industry groups, and technology partners to evaluate emerging AI security capabilities
- At the Sr. Advisor level, serve as enterprise authority on AI security, own the multi-year strategy and investment case, represent Cybersecurity with executives, auditors, and external partners, and set technical direction for advisors and engineers
Requirements
What you’ll need- Bachelor's degree in Computer Science, Cybersecurity, Information Systems, or a related IT technical field
- 10+ years of experience in cybersecurity, security architecture, or platform/software engineering
- Experience in technical leadership, architecture, or senior advisory capacity
- Track record of setting technical direction at enterprise scale and influencing executive investment decisions
- Experience designing or leading security programs across multiple products, teams, or business units
- Strong understanding of cloud security, application security, identity and access management, data protection, and security operations
- Hands-on experience with AI applications, agents, model platforms, LLM APIs, agent frameworks, or agent-to-tool integration protocols
- Strong understanding of LLM-specific threat models, including prompt injection, jailbreaks, sensitive data leakage, tool misuse, excessive agency, data poisoning, and model misuse
- Familiarity with OWASP Top 10 for LLM Applications and MITRE ATLAS
- Ability to evaluate security products and distinguish useful capabilities from features that do not address actual risks
- Proficiency in Python or a comparable language
- Working knowledge of AWS or Azure, REST APIs, and infrastructure-as-code
- Experience building or operating inference-time guardrails, AI gateways, DLP for AI traffic, or AI detection and response tooling at enterprise scale
- Experience with AI security reviews, adversarial red-teaming, or AI governance frameworks in regulated industries
- Experience securing GPU/HPC, model-training, or inference platforms and related data pipelines
- Familiarity with AI regulatory expectations, high-risk AI classifications, auditability requirements, and conformity assessments
- Experience with SIEM/SOAR, EDR, and identity platforms in detection engineering or security operations
- Relevant certifications such as CISSP, CCSP, or cloud security certifications are preferred
- Experience with Agile delivery in cross-functional teams
Benefits
Comp & perks- Company bonus depending on company and individual performance
- Company-sponsored 401(k)
- Pension
- Vacation benefits
- Medical, dental, vision, and prescription drug benefits
- Flexible benefits, including healthcare and/or dependent day care flexible spending accounts
- Life insurance and death benefits
- Time off and leave of absence benefits
- Well-being benefits, including employee assistance program, fitness benefits, and employee clubs and activities