Enterprise AI Security Advisor

Eli Lilly and Company

. Establish and own a companywide approach to securing AI agents, models, applications, and supporting infrastructure .

Posted 10/7/2026full-timeRemote • United StatesSeniorLead💰 $129,000 - $231,000 per yearWebsite

Tech Stack

Tools & technologies

AWSAzureCloudCyber 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 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

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 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

Comp & perks

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