AI Enterprise Architect

Job Description:

AI Enterprise Architect (Strategic Oversight & Governance)

Location: Erskine, Newcastle, Farnborough or London

Candidates are required to be eligible for clearance.

The AI Enterprise Architect defines the target‑state AI architecture and multi‑year roadmap to enable scalable, secure, and governed AI adoption across the enterprise. This senior role provides strategic leadership, vendor and platform guidance, and architectural governance across AI initiatives, ensuring alignment with business strategy, enterprise standards, and regulatory requirements.

• Enterprise AI Architecture &
  
  Roadmap:
  
  Define and maintain the AI reference architecture and implementation roadmap, covering LLM platforms, data pipelines, knowledge graphs, APIs, microservices, and event‑driven architectures across hybrid cloud environments.
• Governance & Standards:
  Establish AI governance frameworks, policies, and playbooks for model development, data usage, security, ethical AI, and compliance.
• Strategic Leadership:
  Provide architectural leadership and direction across delivery teams, ensuring consistent adoption of AI standards and patterns.
• Platform Integration:
  Guide the integration of AI capabilities into core enterprise platforms and processes, enabling reusable AI services and accelerators.
• Security &
  
  Risk Management:
  
  Define and oversee enterprise‑grade security, privacy, and model risk management controls, including monitoring for performance, fairness, and compliance.
• Stakeholder Engagement:
  Lead senior stakeholder discussions, architecture boards, and executive communications.

• Bachelor’s or Master’s degree in Computer Science, Data Science, or related field.
• Deep expertise in AI/ML architectures, including LLMs, data platforms, knowledge graphs, and MLOps concepts.
• Strong understanding of hybrid/multi‑cloud architectures, APIs, microservices, and event‑driven systems.
• Excellent leadership, communication, and stakeholder management skills.
• Proven ability to develop enterprise technology strategy and governance frameworks.

• Strong experience in an enterprise, solution, or data architecture role, including large‑scale AI/ML implementations.
• Experience evaluating and integrating AI platforms and emerging technologies (e.g. generative AI).
• Familiarity with enterprise architecture frameworks (e.g. TOGAF) and cloud architecture certifications.
• Experience operating within governance, risk, and compliance environments (e.g. data protection, AI ethics).