Manager - Cyber Security Engineering and AI Security Lead

About the Role

We are looking for a seasoned Manager to lead our Cyber Security Engineering team, overseeing enterprise-wide security projects with a focus on Application Security, DevSecOps, Cloud Security, and AI Security. This role involves integrating security protocols into software development practices, safeguarding cloud infrastructures, and ensuring compliance with industry and regulatory security frameworks.

Key Responsibilities

• Lead and manage Cyber Security Engineering and DevSecOps efforts across the organization.
• Incorporate security measures within the Software Development Lifecycle and continuous integration/continuous deployment pipelines.
• Oversee Application Security initiatives such as Static and Dynamic Application Security Testing, Software Composition Analysis, threat modeling, and vulnerability management.
• Design and enforce security controls within Azure and AWS cloud platforms.
• Develop AI Security and Governance frameworks following standards like NIST AI Risk Management Framework and ISO/IEC 42001.
• Administer enterprise security tools including SonarQube, Snyk, Microsoft Defender for Cloud, AWS Security Hub, and ServiceNow IRM.
• Collaborate closely with Engineering, Architecture, Infrastructure, Risk, and Compliance teams to ensure secure technology deployments.
• Ensure adherence to regulatory security requirements and assist in security audit processes.
• Provide leadership and mentorship to Cyber Security Engineering teams focusing on continuous improvement and innovation.

Required Qualifications and Skills

• Over 15 years of IT experience with a minimum of 12 years specializing in Cyber Security.
• Extensive hands-on experience in Cyber Security Engineering, DevSecOps, Application Security, and Cloud Security domains.
• Proven expertise in securing Azure and AWS cloud environments.
• Practical experience deploying Secure SDLC practices and integrating security in CI/CD pipelines.
• Strong knowledge of security architectures, vulnerability management processes, API security, container security, and Kubernetes security techniques.
• Experience or familiarity with AI and Large Language Model security as well as AI governance frameworks is highly advantageous.
• Background working within Banking, Financial Services, or other highly regulated industries is preferred.
• Excellent communication, stakeholder engagement, and leadership skills.