Executive Manager - Squad Cyber Technical Lead

Set the technical direction and delivery priorities for application security, AI governance, continuous security validation and compliance-trail workstreams. Convert approved second-line policies into operational controls, measurable service-level outcomes and repeatable delivery practices. Maintain ongoing readiness for supervisory review, including evidence quality, control traceability and timely remediation of identified gaps. Own the architecture, performance and lifecycle of the consolidated cybersecurity tooling environment, including SonarQube, Snyk, ServiceNow IRM, Security Agent, Claude, Codex, OPA, Microsoft Defender for Cloud and AWS Security Hub where relevant. Evaluate vendor consolidation opportunities and define integration patterns that improve visibility, efficiency and control consistency. Design and manage the evidence flow from DefectDojo through attestation and into Power BI governance reporting. Serve as the first-line-of-defence technical counterpart to second-line risk, assurance teams and the AI centre of excellence. Lead the Security Champions Guild, strengthening secure engineering awareness and adoption across delivery teams. Resolve competing demands across the squad and make prioritisation decisions aligned with risk, regulatory obligations and business impact. Present the monthly DevSecOps Governance Dashboard, explaining trends, exceptions, remediation progress and emerging risks to senior stakeholders.

Desired Candidate Profile

Substantial experience leading cybersecurity engineering, security architecture or comparable technical security functions. Strong practical command of DevSecOps, secure software delivery and security engineering across Azure and AWS environments. Demonstrable expertise in AI security, LLM security, AI governance or the implementation of controls for emerging technologies. Professional experience within banking, financial services or another closely regulated industry. Working knowledge of CBUAE Decree-Law 6/2025, the Enabling Technologies Guidelines and the AI/ML Guidance Note, with evidence of applying relevant requirements in practice. Familiarity with the NIST AI Risk Management Framework and ISO/IEC 42001, including their implications for governance, risk and control design. Experience operating effectively within a three-lines-of-defence model and delivering controls from a first-line-of-defence mandate. Confidence engaging second-line stakeholders on policy interpretation, risk acceptance, assurance activity, independent testing and remediation evidence.