AI Security Engineer

Essential qualifications and experience:

• Bachelor's degree in any discipline, or equivalent professional experience; demonstrated engineering practice is the primary criterion.
• Minimum 6 years in security engineering, application security, offensive security, detection engineering or cloud security.
• Minimum 1–2 years of hands-on work securing or testing production generative AI, LLM or agentic systems.
• Demonstrated experience red-teaming AI systems against prompt injection, jailbreaks, excessive agency and model abuse — candidates should be able to walk through specific findings they produced.
• Strong Python, with the ability to build test harnesses, automation and tooling to a production standard.
• Solid cloud security engineering experience on a major hyperscaler; Azure preferred.
• Practical understanding of LLM application architecture: embeddings, vector databases, RAG, agent frameworks, tool and function calling, and the MCP-style integration pattern.
• Working knowledge of OWASP Top 10 for LLM Applications, OWASP agentic security guidance and MITRE ATLAS.
• CI/CD and infrastructure-as-code fluency; comfortable embedding security checks into delivery pipelines.
• Practical use of current AI development tooling — agent-building platforms, AI-assisted coding environments and locally hosted models — to build tooling and evaluation harnesses at speed.
• Clear written reporting — findings must be reproducible and actionable by the receiving team.