Key Responsibilities
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Define and lead the architecture of cloud-native data and AI applications, including AI-powered tools, forecasting solutions and data platforms.
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Translate business needs and technical requirements into robust, scalable and cost-efficient architectures.
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Guide development teams throughout the solution lifecycle, ensuring high engineering standards and quality delivery.
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Establish architectural patterns, reusable components and development guidelines.
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Evaluate technologies and frameworks for application development, AI integration, LLMs and vector-based solutions.
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Promote best practices across cloud infrastructure, application engineering, CI/CD and DevOps.
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Support prototypes, proof of concepts and technology assessments.
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Oversee technical documentation, architectural decisions, project estimations and external technology deliverables.
Key Skills & Experience
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Bachelor's or Master's degree in Computer Science, Engineering or a related field.
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5+ years of experience in cloud-native application architecture, preferably with Microsoft Azure.
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Strong understanding of Microservices, Docker, Containerisation, Serverless, Event-Driven and Service Mesh architectures.
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Experience with Azure services, particularly Azure Container Apps, Azure Functions, Azure SQL and Storage Accounts.
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Python development knowledge (FastAPI, Flask or Django) and familiarity with JavaScript frameworks (React.js, Next.js).
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Strong experience with GitHub, GitHub Actions and CI/CD pipelines.
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Exposure to Azure Databricks, MLflow, RAG, Vector Databases, Azure AI Foundry and AI Agents.
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Understanding of MLOps and Agile methodologies (Scrum/Kanban).
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Excellent communication, analytical and stakeholder management skills.
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Fluent English.