Technical expertise across all areas of AI, including; Machine learning and predictive modelling / MLOps and ML pipeline industrialisation / LLMOps, prompt engineering, embeddings and vector search / Large Language Models (LLMs), hosting, tuning and optimisation / Gen AI and model orchestration / Agentic AI architectures, tool-use patterns, memory and multi-agent workflows
-Knowledge of vector databases, distributed systems and scalable AI workload architecture
-Strong understanding of enterprise data platforms, data sourcing patterns and constraints
-Experience designing scalable cloud-native AI architectures (e.g., Azure, GCP)
-Demonstrable ability to translate complex architectures into reusable enterprise design patterns
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