AI Enterprise Architect

Barclays UK; Knutsford; On-site; GBP 90,000 - 150,000; Full time

Job summary

Barclays is seeking an AI Enterprise Architect in Knutsford to define and govern the bank's data architecture, including standards, models, and shared environments. You will align with the CTO organisation and AI Accelerator to enable enterprise AI capabilities with secure, scalable design.

Responsibilities include leading cross-functional initiatives, communicating AI concepts to senior stakeholders, and ensuring data and AI solutions meet risk, compliance, and strategic goals across business

Qualifications

• Experience with AI/ML architecture, multi-cloud platforms, data architectures and MLOps.
• Knowledge of EA frameworks, AI governance, and compliance in line with business strategy.
• Ability to communicate AI concepts to senior stakeholders and lead cross-functional AI initiatives.

Responsibilities

• Define and govern the bank's target data architecture, including data models and standards.
• Align with CTO organisation and AI Accelerator for enterprise AI capabilities and guard rails.
• Lead cross-functional AI initiatives and ensure risk, controls, and transformation considerations are integrated.

Skills

AI/ML architecture

Enterprise governance

Stakeholder leadership

Job description

Join us at Barclays as an AI Enterprise Architect, where you will drive the definition, direction, and governance of the bank’s target data architecture—including shared data environments, data models, and standards—in support of business strategy. Aligned to the CTO organisation and AI Accelerator, you will support the delivery of enterprise AI capabilities, patterns, and guard rails, ensuring data and AI solutions are accurate, secure, and accessible to stakeholders.

To be successful as an AI Enterprise Architect, you should have experience with:

• AI/ML Architecture: AI/ML frameworks, multi cloud platforms, data architectures, MLOps, and secure, scalable enterprise AI solution design.
• Enterprise Architecture & Governance: EA frameworks, AI governance, ethical AI, compliance, and alignment to business and IT strategy.
• Stakeholder Leadership: Clear communication of AI concepts, senior stakeholder engagement, and leadership of cross-functional AI initiatives.

Some other highly valued skills may include:

• Industry Knowledge: Sector regulations and AI use cases, particularly in regulated industries such as financial services.
• Data Strategy & Analytics: Data management, data quality, analytics platforms, data mesh/fabric, and real-time data processing.

You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job‑specific technical skills