ROLE & RESPONSIBILITIES: Lead design and delivery of end-to-end AI solutions including classical ML models, LLM pipelines, RAGsystems, and multi-agent orchestration.Provide architectural consultation for agentic systems, advising on tool-calling patterns, agent coordination(A2A), memory design, and human-in-the-loop workflows.Design context windows, prompt strategies, and contextual compression techniques to optimise LLM relevanceand cost.Implement document intelligence solutions leveraging embeddings, vector stores, and hybrid retrievalstrategies.Architect and build agentic systems: tool-calling architectures, multi-agent workflows, agent memory, andhuman-in-the-loop pathways.QUALIFICATIONS/EXPERIENCE: Bachelor's degree in Computer Science, Data Science, Mathematics or equivalent experience, with strongbackground in mathematics and analytical problem solving.Proven track record of leading teams, platforms and enterprise deployments handling millions of records inregulated, high-impact environments.Deep hands-on experience across the full lifecycle of modern LLM applications: design, implementation,orchestration, deployment and operational monitoring.