Associate Director, AI Security Frontier Engineering

Responsibilities

• Serve as the primary technical subject matter expert for a designated frontier-AI platform (for example, Anthropic, OpenAI, Microsoft, or Google), owning its security architecture and secure deployment patterns;
• Sequence work against firm priorities and adapt patterns as each platform matures;
• Design and implement automated controls and guardrails across the NIST CSF functions and OWASP Top 10 frameworks, such as mitigating prompt injection, preventing data leakage, and establishing secure model- and tool-interaction patterns;
• Lead complex security engineering initiatives end-to-end with minimal oversight, from risk and gap assessment through control build-out to release criteria; deliver high-quality, defensible capabilities on schedule while operating comfortably in ambiguity;
• Create reusable, cross-platform architecture patterns, control frameworks, and engineering standards so controls built for one AI ecosystem accelerate the next and reduce duplicated effort across concurrent workstreams;
• Lead the development and maturation of security telemetry, monitoring, and detection engineering capabilities by establishing logging standards, onboarding security-relevant data sources, and delivering threat-informed detection content integrated with SIEM and SOC operations; partner with Adversarial Testing teams to validate detection effectiveness, identify visibility gaps, and strengthen defensive controls;
• Establish non-negotiable MVP security and release criteria and hand durable outputs into operations by coordinating detection logic and playbook development with CSIRT and adjacent teams; serve as a technical advisor and mentor, communicating risks and solutions clearly to leadership and engineering peers.

Qualifications

• Minimum eight years of recent progressive experience in security engineering or cloud security, including direct, hands-on experience securing enterprise frontier-AI platforms (such as Anthropic Claude, OpenAI ChatGPT Enterprise/Codex, Microsoft M365 Copilot, or Google Vertex AI/Gemini)
• Bachelor's degree from an accredited college or university in computer science, Cybersecurity, or a related technical field is preferred; minimum of a high school diploma or GED is required; relevant industry certifications such as CISSP, CCSP, or related cloud credentials are highly preferred
• Hands-on expertise securing AI/ML or LLM systems and executing adversarial testing (targeting prompt injection, jailbreaks, data leakage, and tool, plugin, or connector abuse), combined with familiarity with frameworks like NIST AI RMF, MITRE ATLAS, or OWASP Top 10 for LLMs
• Proven track record of independently leading technical initiatives end-to-end and resolving ambiguous, complex problems with minimal oversight, ideally operating in a fast-moving "tiger team" or professional services/highly regulated environment; strong working knowledge of detection engineering and security telemetry (SIEM and logging pipelines), alongside essential enterprise controls including DLP, identity/SSO, and endpoint management
• Excellent communication and collaboration skills to translate complex technical risks for both engineering teams and non-technical senior stakeholders