Enterprise AI Security Advisor
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Job Description
Enterprise AI Security Advisor securing agents, models, and AI infrastructure for Lilly’s global pharmaceutical business. Setting enterprise controls, testing standards, and security strategy.
Responsibilities:
- Establish and own a companywide approach to securing AI agents, models, applications, and supporting infrastructure
- Maintain a prioritized view of AI security risk across commercial AI products, internally built agents, internal models, and AI compute platforms
- 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 covering agent identity, permissions, tool access, data boundaries, human approval, kill switches, 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, including their data access, system access, and possible actions
- Develop and lead testing for prompt injection, sensitive data exposure, excessive permissions, unsafe agent actions, jailbreaks, and misuse scenarios
- Define evidence requirements for moving controls from monitoring to blocking
- Maintain threat models using OWASP Top 10 for LLM Applications and MITRE ATLAS
- Evaluate, select, and tune cloud, endpoint, identity, data protection, and AI-specific security capabilities
- Establish enterprise visibility into 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 development teams to embed security into design, build, and deployment
- Collaborate with privacy, legal, compliance, quality, and AI governance functions
- Mentor engineers and security operations personnel on AI threat models, safe agent design, and responsible AI principles
- Engage vendors, industry groups, and technology partners on emerging AI security capabilities
- At Sr. Advisor level, serve as enterprise authority on AI security, own multi-year strategy and investment case, represent Cybersecurity with executives, auditors, and external partners, and set technical direction
Requirements:
- 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 against organizational risks
- Proficiency in Python or a comparable language
- Working knowledge of AWS or Azure, REST APIs, and infrastructure-as-code
- Ability to work across engineering, infrastructure, security, product, legal, and leadership teams
- Excellent written and verbal communication skills
- 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
- Experience with Agile delivery in cross-functional teams
Benefits:
- Company bonus depending partly on company and individual performance
- Company-sponsored 401(k)
- Pension
- Vacation benefits
- Medical, dental, vision, and prescription drug benefits
- 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
- Disability accommodation support during the application process
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