Senior AI Security Engineer

• AI Security

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.