AI Enterprise Architect

hackajob is collaborating with Barclays to connect them with exceptional professionals for this role.

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.

This role is based out of Knutsford.

To define, direct and govern the bank’s target data architecture (inc. shared data environment, data model and standards) in support of business strategy, ensuring that data is accurate, secure and accessible to meet the needs of 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.
• Emerging Technology:
  Generative AI, LLMs, edge AI, quantum computing potential, AI security, and bias mitigation.

• Development of the banks data architecture strategy, including the translation of bank-wide goals and objectives into target data architecture and transition plan.
• Collaboration with stakeholders, including data operations, engineers and analysts, to provide subject matter expertise and share knowledge to promote standardised, consistent, safe and value-driven data usage.
• Development and maintenance of the banks data architecture governance, standards and protection policies, regarding data models, authoritative data stores, and data capabilities, to support data quality, accuracy and consistency and the protection of sensitive information.
• Management of the alignment of projects to the target data architecture through the provision of guidance, data solutions and monitoring of progress.
• Definition of the shared reusable data capabilities, assets, tools and technologies required to connect disparate data sources, optimise data storage and provide seamless data access.
• Custodianship of an overarching data model that directs how data is logically and physically structured within the banks physical data resources, e.g. database, interfaces and reports.
• Monitoring applicable regulatory standards and industry developments for potential impact on the banks operations, controls and application portfolio.
• Identification and selection of best-in‑class data technologies and ongoing assessment of compliance with the bank's service level agreements and quality standards.