Solution Architect - Data & AI Specialist - Azure ML - AI Foundry - London -Hybrid

W Talent
Greater London, UK
7 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours

Tech stack

Artificial Intelligence Data Analysis Microsoft Online Services Data Governance Software Design Patterns High-Level Architecture Information Lifecycle Management IT Management Cloud Services Azure Machine Learning Systems Integration Zachman Framework
+6 more
IT Architecture Togaf Data Analytics Data Management Machine Learning Operations Databricks

Requirements

Deep domain expertise and demonstrable experience with cloud-based services for data analytics and AI on the Microsoft Cloud (e.g. Azure ML, AI Foundry, Azure Databricks)

Experience shaping proof of concepts and evolve designs to productionised solutions with appropriate AI governance incorporating MLOps and LLMOps to manage risk and auditability

Experience in IT architecture, including applying architectural principles to solution design with a strong focus on designing modern data analytics platforms and AI solutions.

Strong understanding of the data, analytics and AI technology landscape, including the ability to assess existing estates and develop roadmaps focused on reuse, simplification, and rationalisation.

Proven ability to translate business strategies, goals, and requirements into coherent architecture designs, solution blueprints, target architectures and technology roadmaps for data analytics.

Experience shaping enterprise architecture artefacts such as blueprints, technical options, design patterns, high-level designs, for complex data platforms and analytics use cases.

Strong stakeholder engagement skills, including the ability to build and maintain stakeholder maps and communicate architectural outputs effectively.

Experience leading a team of architects, focussing on their personal development and training, and supporting them with their own workload.

Experience representing architecture at governance forums and advocating for strategic solutions.

Experience in IT leadership and management, including the development of highly skilled and engaged teams.

Understanding of best practice across the data lifecycle, including data governance, quality, security, and responsible use of data and AI.

It would also be beneficial, but not necessary, to have some of the following:

Experience working with architectural methodologies and frameworks (e.g. TOGAF, Zachman) and experience in architecture modelling tools

Enterprise Architecture skills such as technical reference model development, building block design, applications and role design, systems integration, and evaluation of architectures.

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