Nurture and develop a high performing team and develop relationships across the wider Sopra Steria organisation.
Support the development of, understand and absorb, and contribute to review and cascade of business requirements.
Propose optimal solutions and lead the design and creation of design artefacts across pre-sales, delivery and as repeatable blueprints.
Make day to day decisions regarding the setup and priorities for the architecture community along with their required leadership team to govern and direct resources within it.
Build and the support the development of compelling propositions to take to market in the field of AI & Data.
Leading technical design and authoring on bids and proposals to customers.
Collaborate with initiative leads and steering groups to ensure the right skills are maintained within the architecture function.
Build and maintain strong, long-lasting customer relationships.
Requirements & Skills:
A proven record in enterprise and solution architecture.
Growth and bid experience from consultancy-style customer engagements through owning the solution for large and complex architectures.
A domain expert in Artificial Intelligence, Machine Learning (ML) and data lead solutions and regarded as a lead presence.
Familiarity with technical design standards and core technical principles, architectural and engineering methods, governance and development of repeatable reference architectures and blueprints.
Robust knowledge of data and artificial intelligence standards.
Artificial Intelligence and ML e.g. AWS Sagemaker, AWS Bedrock, Azure AI Platform / ML and Jupyter.
Knowledge of GenAI and LLM’s such as ChatGPT, Claude, Llama and OpenAI with advanced features such as prompt engineering, fine tuning, and Retrieval Augmented Generation (RAG) and advances search
Intelligent document processing using AI including OCR, handwriting character recognition and computer vision.
Digital assistant solutions enhanced by AI to interact with users across a number of channels including chat, voice and application native integration such as Microsoft Copilot.
Data architectures including data integration, management, reporting and analytics, simulation and digital twins.
Data pipeline development including data and AI Operations using tools such as Argo, AirFlow, MIFlow, Superset and DebiAI.
Cloud native delivery engineering such as Containers / Kubernetes, event driven architecture, microservices and Prometheus
