Corporate Security Engineer, AI

We are looking for a Corporate Security Engineer, AI to own the security of how artificial intelligence is adopted and operated across Capital.com.

AI tools are already embedded in how the company works — and the security risks they introduce are unlike those any other team currently owns. This role sits in Corporate Security and is responsible for AI system integration security, AI-specific threat detection, data protection in AI contexts, shadow AI governance, and the regulatory compliance obligations that AI adoption brings with it.

The ideal candidate understands how LLMs, RAG systems, and AI automation tools actually work — and can apply that understanding to evaluate what risks they introduce, design controls that hold, and build the governance framework that makes AI adoption secure and auditable in a regulated financial services environment.

• 3–5+ years in cybersecurity with hands-on experience in AI/ML system security or a strong AI security focus;

• Deep knowledge of AI-specific security risks and mitigations: prompt injection, model poisoning, data leakage, adversarial attacks, excessive permissions in AI agents;

• Hands-on experience securing LLM integrations, RAG pipelines, and AI APIs — reviewing configurations, access controls, and data flows;

• Experience authoring AI security policies, standards, and risk classification frameworks;

• Familiarity with AI governance frameworks: EU AI Act, NIST AI RMF, ISO/IEC 42001, and their application in a regulated financial services context;

• Experience running AI risk assessments and maintaining an AI risk register;

• Ability to manage third-party AI tool due diligence and control shadow AI across a distributed workforce;

• Python proficiency for automation and scripting.

• Recognised certifications: CISM, CISSP, or equivalent;

• Experience in fintech or a regulated financial services environment;

• Multi-jurisdiction compliance exposure (FCA, CySEC, ASIC, SCB, or SCA);

• Experience building AI-powered security automation — autonomous agents, LLM-driven triage, automated response workflows;

• Experience presenting AI security risk posture to leadership or board-level audiences.

• Strong analytical and problem-solving skills;

• Ability to translate technical AI risk into business and regulatory impact;

• Able to explain AI security risks and mitigations to non-security teams;

• Cross-functional collaboration with risk, compliance, product, and engineering teams;

• Clear documentation and communication skills.