We are looking for an Enterprise Architect specializing in Data & AI to join our architecture team and help shape our enterprise-wide data and AI landscape.
In this role, you will define and evolve the architecture vision for data, analytics, AI, and Generative AI, ensuring that platforms and capabilities are scalable, secure, well-governed, and aligned with business priorities.
You will work at the intersection of business strategy, enterprise architecture, data engineering, and AI/ML, translating strategic objectives into architecture principles, target-state architectures, technology roadmaps, and practical guidance for delivery teams.
Key Responsibilities
- Vision & Roadmap: Define and evolve the enterprise Data & AI architecture vision, including target-state architectures, reference architectures, architecture principles, and technology roadmaps.
- Data Architecture & Standards: Establish and promote standards for data modelling, governance, master data management, data quality, metadata management, and data lifecycle management.
- Data Platforms: Design and validate architectures for modern data platforms, including data lakes, data warehouses, lakehouses, and streaming solutions across cloud, hybrid, and where relevant on-premises environments.
- AI & ML Architecture: Define architecture patterns for AI and ML capabilities, including MLOps, model lifecycle management, model monitoring, and integration with enterprise data platforms.
- Generative AI: Define scalable and secure architecture patterns for Generative AI and LLM-based solutions, including RAG, enterprise data integration, model access, orchestration, and governance.
- Business Alignment: Partner with business and technology stakeholders to translate strategic objectives and use cases into Data & AI capabilities and architecture roadmaps.
- Architecture Governance: Guide project and engineering teams on architecture decisions, facilitate architecture reviews, and promote alignment with enterprise standards and design principles.
- Technology Evaluation: Assess technologies, platforms, and vendors across cloud, data, analytics, AI, and machine learning, balancing business value, technical fit, security, cost, and long-term sustainability.
- Data & AI Governance: Ensure that privacy, security, responsible AI, and applicable regulatory requirements are considered throughout architecture and design decisions.
- Responsible AI: Help define architecture guardrails around model risk, transparency, explainability, monitoring, and responsible use of AI.
- Technical Leadership: Act as a trusted architecture advisor to data engineering, analytics, AI, and data science teams, sharing best practices and supporting complex architecture decisions.
- Enterprise Collaboration: Work closely with fellow enterprise architects across applications, infrastructure, security, integration, and cloud to ensure architectural coherence.
- Innovation & Technology Watch: Stay informed about developments in data platforms, AI/ML, and Generative AI and assess where emerging technologies can create meaningful value for the organisation.