AI Security Testing Lead

AI Security Assessment Lead

Lead and execute AI security assessments of Copilot-like apps, LLM applications, RAG pipelines, and agent/tool integrations. Formalize and operationalize an AI testing methodology (scope ? test plan ? execution ? reporting ? retest) suitable for regulated enterprise use. Stand up and mature non-prod AI testing infrastructure and repeatable workflows (safe test data, access patterns, evidence capture, reusable harnesses). Enable existing pentesters via training, playbooks, reusable test packs, and quality review of findings/evidence. Drive governance and defensibility: human-in-the-loop decisions, safe testing constraints, reproducible evidence, and consistent severity rationale. Communicate outcomes to technical teams and leadership: themes, control gaps, remediation priorities, and validation results.

Demonstrated hands-on experience assessing AI-enabled applications, including one or more of:

• LLM application security testing (prompt injection, data leakage, insecure output handling)
• RAG security testing (retrieval manipulation, ingestion risks, exposure paths)
• Agent/tool integration testing (tool boundary violations, unintended actions, privilege misuse)

Strong understanding of AI/LLM risk categories and how they translate into enterprise impact (confidentiality, integrity, availability, operational risk, and regulatory/audit concerns). Ability to design safe, controlled testing approaches for AI systems (rules of engagement, non-prod usage, safe test data, rate/cost controls where applicable).

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