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 supporting infrastructure across the organization.

• Maintain a prioritized overview of AI security risks for commercial AI products, internally developed agents, internal models, and AI computing platforms.

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

• Advise senior management on emerging AI threats, balancing safety and productivity trade-offs, and prioritizing investment opportunities.

• Define security requirements and approved standards encompassing agent identity, permissions, tool access, data boundaries, human approvals, kill switches, logging, monitoring, and incident response.

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

• Establish control expectations for inference-time guardrails, AI gateways, as well as 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, including their data access, system access, and potential actions.

• Develop and oversee testing strategies for prompt injection, sensitive data exposure, excessive permissions, unsafe agent actions, jailbreaks, and misuse scenarios.

• Define evidence requirements necessary for transitioning controls from monitoring to blocking.

• Maintain threat models utilizing OWASP Top 10 for LLM Applications and MITRE ATLAS.

• Evaluate, select, and optimize security capabilities related to cloud, endpoint, identity, data protection, and AI.

• Establish organizational visibility into AI usage and agent activities.

• 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.

• Develop detection, alerting, and incident response playbooks tailored for AI-specific events.

• Collaborate with AI application and agent development teams to integrate security into the design, build, and deployment processes.

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

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

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

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

⛳️ Requirements

• 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 technical leadership, architecture, or a senior advisory role.

• A history of establishing technical direction at an enterprise scale and influencing executive-level investment decisions.

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

• Strong knowledge 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 protocols for agent-to-tool integration.

• In-depth 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.

• Capability to assess security products against organizational risks.

• Proficient in Python or a similar programming language.

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

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

• Excellent written and verbal communication skills.

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

• Experience with AI security reviews, adversarial red-teaming, or AI governance frameworks in regulated sectors.

• Background 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.

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

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

• Experience with Agile methodologies in cross-functional team environments.

🏝️ Benefits

• Company bonus that is partly based on both company and individual performance.

• Company-sponsored 401(k) plan.

• Pension plan.

• Vacation benefits.

• Comprehensive medical, dental, vision, and prescription drug benefits.

• Flexible spending accounts for healthcare and/or dependent daycare.

• Life insurance and death benefits.

• Time off policies and leave of absence benefits.

• Well-being initiatives, including an employee assistance program, fitness benefits, and opportunities for employee clubs and activities.

• Disability accommodation support during the application process.