AI Security Engineer

• Develop and implement robust security frameworks specifically designed for AI/ML models, ensuring their integrity and preventing adversarial attacks. • Conduct in-depth security assessments of AI systems, identifying vulnerabilities in data pipelines, model architectures, and deployment environments. • Design and deploy advanced threat detection and response mechanisms tailored to the unique attack vectors targeting AI systems. • Implement data privacy and compliance measures for AI/ML projects, adhering to regulations like GDPR and CCPA. • Minimum Experience At least 4 years of experience in cybersecurity, cloud security, application security, security engineering, DevSecOps or security operations, including hands-on experience securing Generative AI, machine-learning or other emerging technology solutions. Practical experience designing and implementing security controls in major cloud environments. Experience with threat modelling, security architecture reviews, vulnerability assessments and adversarial or red-team testing. Experience developing scripts, tools or automation and working with engineering teams in complex enterprise environments, preferably in financial services. Minimum Qualifications Bachelor’s degree in Cybersecurity, Information Security, Computer Science, Computer Engineering, Software Engineering, Information Technology, Data Science, Artificial Intelligence, Machine Learning, or another relevant technical discipline. Postgraduate qualification in Cybersecurity, Artificial Intelligence, Machine Learning, Computer Science, Software Engineering, or a related technical discipline is preferred. Professional Qualifications Relevant professional certifications in cloud security, security operations, AI security or AI governance are preferred. Examples include Microsoft SC-100, SC-200, SC-300, AI-102 and AZ-500; CISSP, CCSP, CSSLP, OSCP, relevant GIAC certifications (for example GPCS, GCSA, GMLE), ISO/IEC 42001 Lead Implementer or Lead Auditor, AI governance certifications such as AIGP, and CISA or CRISC. Knowledge and Skills AI, Agentic AI and ML Security Agentic AI architectures, LLM and Generative AI security, ML security, prompt injection and jailbreak defences, guardrails, RAG security, MCP and tool-access security, adversarial machine learning, and AI supply chain security. Familiarity with MITRE ATLAS, the OWASP Top 10s. Microsoft Security and Cloud Microsoft Entra, Defender (XDR, Cloud, Identity), Sentinel (KQL, analytics rules), Purview (DLP, information protection, data governance), Security Copilot and agentic SOC capabilities, Azure AI Foundry and Azure OpenAI security. AI-driven Cybersecurity Developing AI solutions for defensive and offensive security engineering (e.g., detection engineering, threat intelligence, vulnerability management, red-teaming). Governance and Risk ISO/IEC 27090, ISO/IEC 42001, ISO/IEC 27001, NIST AI Risk Management Framework, and the ability to map technical controls to regulatory and policy requirements. Skills Generative AI Security Cloud Security DevSecOps