Head of Security Architecture in London

The Head of Security Architecture with deep expertise in AI systems to design, implement, and maintain secure architectures for enterprise security, artificial intelligence and machine learning initiatives across the organisation. This role will define technical security standards, reference architectures, and implementation frameworks that protect traditional IT environments and AI systems, models, data pipelines, and deployments throughout their life-cycle — from conception to production. The Head of Security Architecture will partner with stakeholders and internal teams to establish a comprehensive, forward-looking security strategy and architecture that enables organisational ambitions while managing AI-related security risks.

What you’ll be doing

• Work with stakeholders and internal teams to define a comprehensive, forward-looking Security strategy, inclusive of AI Security and Architecture that supports the organisation's global growth ambitions, incorporating policies, standards, and control frameworks applicable across multiple jurisdictions.
• Establish and evolve governance mechanisms that promote responsible, ethical, and compliant AI use worldwide, considering regional regulatory nuances and cultural sensitivities.
• Integrate AI security requirements into security and enterprise architecture, software development life cycles, and model life‑cycle management, ensuring consistency and agility across diverse operational regions.
• Will be part of Security Strategy development and does require interaction with executive business leaders for a global organisation.

Architecture & Design:

• Design enterprise‑wide security architectures and reference implementations.
• Establish secure AI development, training, and deployment pipelines.
• Define AI & security data governance and access control frameworks for systems.
• Create security‑by‑design principles for AI model development.
• Design threat models specific to AI/ML systems and attack surfaces.

Technical Security Standards:

• Develop and maintain security frameworks and best practices.
• Create secure coding standards for ML engineers and data scientists.
• Establish model validation, testing, and verification protocols.
• Define encryption, authentication, and authorisation standards for systems.
• Document security requirements and technical specifications.

Infrastructure & Systems:

• Architect secure AI infrastructure (cloud, on‑prem, hybrid).
• Design model registry, versioning, and deployment systems with security controls.
• Implement monitoring, logging, and anomaly detection for AI systems.
• Oversee secure data pipelines and feature stores.
• Design isolation and sandboxing for high‑risk AI workloads.

Risk & Threat Mitigation:

• Conduct threat modelling for AI systems (adversarial attacks, model poisoning, data poisoning).
• Design defences against AI‑specific vulnerabilities.
• Implement model robustness testing and validation frameworks.
• Create incident response architectures for AI security breaches.
• Design recovery and rollback mechanisms for compromised models.

Vendor & Third‑Party Management:

• Evaluate and architect integrations with third‑party AI platforms securely.
• Define security requirements for AI vendors and SaaS providers.
• Design secure APIs and interfaces for external AI model access.
• Oversee security architecture of outsourced AI development.

Governance & Compliance:

• Align security architecture with regulatory requirements (GDPR, AI Act, industry standards).
• Design audit trails and compliance monitoring systems.
• Document architecture decisions and security trade‑offs.
• Collaborate on responsible AI and ethical AI architecture considerations.

Team Leadership & Knowledge Sharing:

• Lead AI security architecture reviews and design sessions.
• Mentor security engineers and architects.
• Present architecture recommendations to technical and executive stakeholders.
• Build and maintain security architecture documentation.
• Drive adoption of secure architecture patterns.

What you’ll bring

• Substantial experience in cyber security, systems architecture, or infrastructure security.
• Proven capabilities in designing and architecture large‑scale systems.
• Experience in hands‑on and applied experience with AI/ML security architecture.
• Deep technical knowledge of:
• Machine learning systems and workflows.
• AI/ML vulnerabilities and attack vectors (adversarial examples, model extraction, poisoning).
• Cloud security and containerisation (Docker, Kubernetes).
• Data security, encryption, and access controls.
• API security and micro‑services architecture.
• Robust background in threat modelling and security architecture frameworks.
• Experience with secure software development life‑cycle (SSDLC).
• Advanced degree in Computer Science, Cyber security, or related field (or equivalent).

Key Competencies

• Executive judgement and credibility.
• Global risk thinking and cultural agility.
• Governance and control design.
• Influencing and stakeholder management without direct authority.
• Clear, compelling communication tailored for diverse audiences, including boards and regulators.
• Balancing innovation with disciplined risk management on a global scale.

Preferred Skills

• CISSP, CCSK, CISM, AAISM or similar security architecture certification.
• Experience with MLOps/MLSecOps platforms.
• Background in machine learning engineering or data science.
• Experience with AI governance and responsible AI frameworks.
• Knowledge of AI‑specific security standards (NIST AI RMF, ISO/IEC 42001).
• Experience in regulated industries (finance, healthcare, government).
• Contributions to open‑source security or AI security projects.
• Speaking/publishing on AI security topics.