Enterprise AI Security Advisor

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop and take ownership of a comprehensive strategy for securing AI agents, models, applications, and their supporting infrastructure.

• Sustain a prioritized assessment of AI security risks associated with commercial AI products, internally developed agents, in-house models, and AI computing platforms.

• Manage the roadmap for AI security controls, tools, and enhancements; provide updates and measurable results to leadership.

• Counsel senior leadership on emerging AI threats, balancing safety and productivity trade-offs, as well as investment priorities.

• Establish security requirements and sanctioned patterns for AI systems, encompassing identity, permissions, data access, human approval, kill switches, logging, monitoring, and incident response.

• Publish reference architectures and acceptance criteria for AI applications, agents, and integrations.

• Set expectations for controls related to inference-time guardrails, AI gateways, and model and agent registries.

• Incorporate AI security requirements into security architecture reviews, risk acceptance, and change management processes.

• Evaluate both internally developed AI systems and third-party AI products to identify necessary controls.

• Create and lead testing for scenarios involving prompt injection, sensitive data exposure, excessive permissions, unsafe agent behavior, jailbreaks, and misuse situations.

• Specify evidence needed before transitioning controls from monitoring to blocking.

• Maintain threat models for high-value AI systems using OWASP Top 10 for LLM Applications and MITRE ATLAS.

• Assess, select, and optimize cloud, endpoint, identity, data protection, and AI-focused security capabilities.

• Ensure visibility into enterprise AI usage and agent activities.

• Lead enterprise AI guardrail services, which include detection content, policy tuning, telemetry, dashboards, and integrations with SIEM, SOAR, EDR, identity, and ticketing platforms.

• Establish detection, alerting, and incident response protocols for AI-specific events.

• Collaborate with AI engineering teams to embed security in the design, development, and deployment processes.

• Work alongside privacy, legal, compliance, quality, and AI governance functions.

• Mentor engineers and security operations staff on AI threat models, safe agent design, and responsible AI principles.

• Engage with vendors, industry groups, and technology partners regarding emerging AI security capabilities.

• At the Senior Advisor level, act as the enterprise authority on AI security, oversee multi-year strategy and investment cases, represent Cybersecurity to executives, auditors, and external partners, and define technical direction.

⛳️ Requirements

• A Bachelor's degree in Computer Science, Cybersecurity, Information Systems, or a related technical field in IT.

• Over 10 years of experience in cybersecurity, security architecture, or platform/software engineering.

• Proven experience in a technical leadership, architectural, or senior advisory role.

• Demonstrated ability to set technical direction at an enterprise level and influence executive investment decisions.

• Experience in designing or leading security programs across various products, teams, or business units.

• Strong understanding of cloud security, application security, identity and access management, data protection, and security operations.

• Practical experience with AI applications, agents, model platforms, LLM APIs, agent frameworks, or agent-to-tool integration protocols.

• In-depth knowledge 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 assess security products and differentiate useful capabilities from features that do not mitigate actual risks.

• Proficient in Python or a similar programming language.

• Working knowledge of AWS or Azure, REST APIs, and infrastructure-as-code.

• Experience in building or managing inference-time guardrails, AI gateways, DLP for AI traffic, or AI detection and response tools at an enterprise level.

• Familiarity with AI security reviews, adversarial red-teaming, or AI governance frameworks within regulated sectors such as pharmaceuticals or healthcare.

• Experience in securing GPU/HPC, model-training, or inference platforms, along with associated data pipelines.

• Understanding of AI regulatory expectations, high-risk AI classifications, auditability requirements, and conformity assessments.

• Familiarity with SIEM/SOAR, EDR, and identity platforms in a detection engineering or security operations context.

• Relevant certifications such as CISSP, CCSP, or other cloud security certifications.

• Experience with Agile delivery in cross-functional teams.

• Ability to collaborate across engineering, infrastructure, security, product, legal, and leadership teams.

• Excellent written and verbal communication skills.

• Capability to articulate AI risk to both technical and business audiences.

🏝️ Benefits

• Company bonus based on both individual and company performance.

• Company-sponsored 401(k) plan.

• Pension plan.

• Vacation benefits.

• Medical, dental, vision, and prescription drug plans.

• 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 an employee assistance program, fitness benefits, and opportunities for employee clubs and activities.