Senior Staff AI Security Lead

Role overview

A senior technical leader is needed to build the AI foundation for a security organization and drive its adoption across teams. This is a dual-mandate, hands-on individual contributor role with an even split between platform engineering and enablement work. The position reports to security leadership and partners closely with Platform Engineering, IT, Legal, Privacy, and broader AI/ML groups.

Responsibilities

- Design and build a shared platform for security AI applications, including model gateway and routing, authentication, secrets handling, rate limiting, cost attribution, and audit logging. - Establish patterns and reusable components for agentic workflows, including tool and MCP server integration, sandboxed execution, human-in-the-loop approval gates, and least-privilege scoping. - Connect security knowledge bases (runbooks, detection logic, past incidents, asset inventory, policy documents) to AI systems through well-governed retrieval pipelines with access controls and data classification. - Build evaluation harnesses, regression suites, and observability tooling to measure output quality, latency, cost, hallucination rate, and drift; ensure nothing ships without a baseline. - Implement guardrails against prompt injection, data exfiltration, insecure tool use, and supply-chain risk; red-team the platform and dependent applications. - Work directly with detection engineering, incident response, threat intel, vulnerability management, GRC, and security operations to identify high-value AI use cases and deliver flagship applications that drive adoption.

Requirements

- 8+ years in security engineering, platform engineering, or a closely related technical field, with significant hands-on software development experience. - Demonstrated experience building and operating production systems with large language models, including shipping real applications and iterating on failure modes. - Strong software engineering fundamentals and fluency in Python or equivalent, with experience in API design, distributed systems, and cloud infrastructure (AWS, GCP, or Azure). - Deep understanding of security engineering: identity and access management, secrets management, network boundaries, logging and detection, and secure software development. - Working knowledge of AI-specific risks, including prompt injection, jailbreaks, data leakage through model outputs, insecure agent tool use, and model or dependency supply chain, with practical mitigations. - Track record of driving technical change through influence rather than authority, with clear written and verbal communication skills across engineering and executive audiences.

Benefits and work setup

- Location is flexible: onsite, hybrid, or fully remote for the right candidate. - Travel up to 10%. - The organization is committed to equal employment opportunity and a culture of autonomy, productivity, and respect, with explicit non-discrimination policies. - Export-control and government-contract restrictions may apply; candidates may need to verify status as a U.S. person, U.S. citizen, U.S. national, U.S. permanent resident, refugee, or asylee depending on the role's technical scope.