Lead, Offensive Security

About the role

We're standing up a new AI & Offensive Tooling capability inside our Offensive Security organization, and we're looking for its founding engineer. As Lead, Offensive Security (AI & Tooling), you will own the in-house AI agent platform that powers our penetration testing and red team operations, and build the AI-driven tooling that makes every offensive service line faster, broader, and more autonomous.

Responsibilities

• Ramp on the agent platform and the three service lines (Red Team, BAS, Penetration Testing)
• Take operational ownership
• Ship one meaningful improvement to the agent's autonomous capability or reliability, measured against real engagements
• Deliver at least one AI-driven tool that a service line adopts into its live workflow, with metrics showing coverage or turnaround gains
• Establish the evaluation harness that tracks the agent's autonomous success rate against representative targets
• Publish the multi-quarter offensive-AI roadmap and KPIs
• Stand up repeatable adversarial testing for the enterprise's own AI systems
• Mentor 1–3 engineers as the capability grows toward its own function

Requirements

• Offensive security depth: 6+ years in roles such as Red Team or Penetration Testing, including team- or program-level leadership, and the instinct to think like an attacker against systems that don't behave deterministically
• Production Python engineering: a strong track record of building and operating production-quality software and tooling, not only scripts
• Hands-on designing, building, or operating AI agents or LLM applications: agentic workflows, tool/function-calling, and orchestration
• Hands-on testing of AI/ML systems: prompt injection, jailbreaking, and adversarial techniques
• Cloud fluency: production experience with at least one major Cloud Service Provider (AWS, GCP, or Azure)

Qualifications

• Built autonomous or semi-autonomous offensive agents, LLM-driven penetration-testing agents, or reinforcement-learning exploit and attack-path planners
• Fluent in MITRE ATLAS, the OWASP Top 10 for LLM Applications, and the NIST AI Risk Management Framework
• Model Context Protocol (MCP): building clients/servers, or testing them and RAG pipelines for tool/prompt-injection abuse
• Demonstrated ability to test endpoints protected by modern EDR/XDR; experience across multiple cloud providers; threat-intelligence-driven operations
• Depth in an advanced offensive specialty: malware development, advanced Red Team operations and threat simulation, or adversarial ML research; experience building and breaking LLMs, ML models, and AI infrastructure
• Published research, open-source contributions, or talks at DEF CON, BSides, x33fcon, or Black Hat; expert-level certifications (e.g. OSEE, OSED, OSCE3, CRTL, CWEE, CAPE)