Offensive Security Agent Engineer
New
O
OpenAISecurity / AI
Remote - USFull-TimeStaff
Salary$347K - $490K
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Job Details
- Required Skills
- KubernetesLinuxSoftware Engineering
Requirements
- Substantial hands-on offensive security experience.
- Extensive domain expertise in cloud security, Kubernetes and container security, web application security, source-code review, Linux security, macOS security, or external attack-surface testing.
- Experience assessing complex, highly customized environments.
- Proven ability to decompose ambiguous security problems into reliable systems.
- Experience building production-quality software.
- Demonstrated experience building or extending agent systems that use models, tools, structured context, memory, orchestration, and feedback loops.
- Deep understanding of evaluations, observability, failure recovery, safety, maintainability, and regression resistance.
- Strong intuition for model capabilities and limitations.
- Experience partnering with infrastructure, product, and engineering teams.
Responsibilities
- Serve as the technical owner of OpenAI’s offensive security agents, establishing its architecture, technical direction, operating model, and evaluation strategy.
- Design and build a portfolio of specialized agents that continuously test OpenAI’s infrastructure and applications from a variety of authenticated and unauthenticated perspectives.
- Translate expert offensive security workflows and intuition into tools, skills, harnesses, policies, and internal knowledge bases.
- Develop capabilities for testing cloud and Kubernetes environments, modern web applications, external attack surface, endpoints, and other high-value systems.
- Build complete vulnerability-management loops that move beyond discovery to impact validation, ownership identification, prioritization, remediation support, progress tracking, and fix verification.
- Design human-in-the-loop systems that allow offensive security engineers to approve or reject potentially dangerous actions, provide missing context, redirect investigations, and steer agents away from unproductive paths.
- Create feedback mechanisms that allow agents to learn from the decisions, corrections, and domain expertise of experienced offensive security practitioners.
- Develop rigorous evaluations that measure meaningful security outcomes and improvements in agent capability over time.
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