Enterprise Architect
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Role details
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Job description
AI Architect Job Description: Essential Skills/Experience - Enterprise Architecture experience: proven EA leadership translating concepts into production-ready solutions.- Hands-on AI/ML engineering: building, fine-tuning, and deploying ML/DL models (LLMs, RAG, MLOps) in production.- AI platforms: hands-on with AWS (Bedrock, SageMaker, Amazon Q), Azure (Azure AI, ML, OpenAI), and Databricks.- Engineering and analytics: strong Python, TensorFlow/PyTorch, containers, Kubernetes, and CI/CD for hybrid cloud.- Data modelling and governance: conceptual/logical modelling and governance standards in regulated environments.- Architecture judgement: select fit-for-purpose AI architecture per use case, with full-lifecycle understanding.- Leadership: lead a small team of AI architects and help shape enterprise AI strategy and direction.- Degree in data science, AI engineering, or a related field (or equivalent experience).Desirable Skills/Experience - Postgraduate degree in MIS, AI, data science, or a related field.- Recognised thought leader in applying AI within the enterprise and across the industry.- Extensive senior AI, data science, data engineering, and AI architecture experience delivering large-scale blueprints.- Hands-on building AI models, including LLMs and LVMs, across diverse data types
Requirements
AI Architect Job Description: Essential Skills/Experience - Enterprise Architecture experience: proven EA leadership translating concepts into production-ready solutions.
- Hands-on AI/ML engineering: building, fine-tuning, and deploying ML/DL models (LLMs, RAG, MLOps) in production.
- AI platforms: hands-on with AWS (Bedrock, SageMaker, Amazon Q), Azure (Azure AI, ML, OpenAI), and Databricks.
- Engineering and analytics: strong Python, TensorFlow/PyTorch, containers, Kubernetes, and CI/CD for hybrid cloud.
- Data modelling and governance: conceptual/logical modelling and governance standards in regulated environments.
- Architecture judgement: select fit-for-purpose AI architecture per use case, with full-lifecycle understanding.
- Leadership: lead a small team of AI architects and help shape enterprise AI strategy and direction.
-
Degree in data science, AI engineering, or a related field (or equivalent experience). Desirable Skills/Experience - Postgraduate degree in MIS, AI, data science, or a related field.
- Recognised thought leader in applying AI within the enterprise and across the industry.
- Extensive senior AI, data science, data engineering, and AI architecture experience delivering large-scale blueprints.
- Hands-on building AI models, including LLMs and LVMs, across diverse data types
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