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Database • Analytics
Leads the technical direction, architecture, quality, and growth of an AI Engineering practice. Designs production AI systems, guides major client engagements, conducts design reviews, resolves complex engineering challenges, shapes proposals and delivery plans, and develops senior technical talent. The role remains hands-on with Python, AI architectures, retrieval, agentic pipelines, evaluation, scalability, reliability, and observability. It also requires client-facing leadership, commercial awareness, capability planning, and experience with Databricks and Azure OpenAI.
Database • Analytics
Lead discovery and shape AI product strategy by identifying high-value AI opportunities, creating business cases and roadmaps, mobilising cross-functional teams, validating technical feasibility, and establishing governance to deliver scalable, measurable AI solutions.
