AI Cybersecurity Architect – Governance, Control Frameworks

Xenon Seven

AI Cybersecurity Architect shaping AI security governance and control frameworks for a major Egyptian banking institution. Establishing policies and technical controls for secure AI and ML implementations.

Posted 7/7/2026contractRemote • 🇮🇳 IndiaSeniorLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in establishing AI Security Governance Frameworks and designing cybersecurity controls tailored for AI/ML systems. Possesses a strong understanding of regulatory compliance within the financial sector, particularly in relation to CBE regulations and data protection laws.

Highest-signal resume keywords

AI Security Governance FrameworksCybersecurity ArchitectureAI/ML Systems SecurityCBE Cybersecurity ComplianceRisk Assessment and Threat Modeling

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Applicant Tracking System Keywords

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Hard Skills

Cybersecurity Control FrameworksAI/ML InfrastructureData Ingestion and TrainingModel Integrity VerificationVulnerability ScanningNIST SP 800-53ISO 27001Data Poisoning PreventionPrompt Injection MitigationAPI Integration Security

Soft Skills

Exceptional CommunicationStakeholder ManagementProfessional Maturity

Tools & Technologies

AzureAWSHybrid EnvironmentsVector DatabasesLLM Orchestration Layers

Certifications & Qualifications

CISSPCISMCRISCCCSPAI Security Credentials

Industry Keywords

Central Bank of EgyptEgyptian Data Protection LawFinancial Institution ComplianceCybersecurity CircularsAuditing Standards

Tech Stack

Tools & technologies

AWSAzureCloudCyber Security

About the role

Key responsibilities & impact

Establish AI Security Governance Frameworks: Author, implement, and maintain the bank's enterprise-wide AI Security Policy. Align our internal AI governance with international standards (such as NIST AI RMF, ISO/IEC 42001, and OWASP Top 10 for LLMs) while strictly ensuring compliance with evolving Central Bank of Egypt (CBE) regulations and the Egyptian Data Protection Law.
Design & Build Cybersecurity Controls: Architect, enforce, and validate technical and administrative security controls tailored for the entire AI/ML lifecycle (Data Ingestion, Training, Deployment, and Inference). This includes building robust controls against data poisoning, model inversion, prompt injection, and unauthorized data exfiltration.
Secure MLOps Architecture: Define the reference architectures and secure guardrails for our Machine Learning Operations (MLOps) pipelines. Ensure that security checks, vulnerability scanning, and model integrity verifications are seamlessly integrated into our continuous deployment workflows.
Advanced AI Threat Modeling & Risk Assessment: Lead comprehensive risk assessments and threat-modeling exercises on all proprietary and third-party AI implementations. Identify structural risks in algorithmic logic, training data pipelines, and API integrations, translating technical risks into clear business governance metrics.
Third-Party & Vendor AI Governance: Develop and execute rigorous cybersecurity assessment frameworks for evaluating third-party AI tools, cloud-hosted models, and external vendors, ensuring they meet the bank’s strict data privacy and control standards.

Requirements

What you’ll need

8+ years of progressive experience in Cybersecurity Architecture or IT Risk Governance, with at least 3+ years of dedicated experience explicitly focused on securing AI/ML systems and building enterprise governance frameworks.
Minimum of 3 years of experience working within a regulated financial institution in Egypt. You must possess an intricate understanding of CBE cybersecurity circulars, auditing standards, and banking compliance requirements.
Proven track record of designing, writing, and implementing complex cybersecurity control frameworks from scratch. Deep familiarity with traditional frameworks (NIST SP 800-53, ISO 27001) as well as modern AI-specific guardrails is a must.
Strong conceptual and practical understanding of AI/ML infrastructure, including neural networks, LLM orchestration layers, vector databases, and cloud data platforms (Azure, AWS, or hybrid environments). You must speak the language of both data scientists and enterprise security engineers.
Bachelor’s degree in Cybersecurity, Computer Engineering, Computer Science, or a related technical discipline.
Elite security certifications are highly preferred (e.g., CISSP, CISM, CRISC, or CCSP), alongside any specialized AI security credentials.
Exceptional communication and stakeholder management skills. You must possess the professional maturity to present complex AI risks to C-suite executives and board members, while maintaining the technical credibility to influence data science teams. Fluency in English.

Benefits

Comp & perks

Attractive, market-leading salary package
Clear career advancement path with professional development opportunities