•Open-Source Ecosystems: Familiarity with community-driven AI tools and libraries, including Hugging Face and relevant repositories
•T-shaped Profile: Deep technical expertise in one or two domains, with broad understanding across AI/ML, cloud, and consulting
•Agentic AI Systems: Experience designing, building, or integrating multi-agent systems and orchestration frameworks (e.g., LangGraph, Semantic Kernel, Agent Framework, AutoGen, CrewAI), including the development of agent protocols and coordination mechanisms
•Retrieval-Augmented Generation (RAG) & Knowledge Systems: Practical knowledge of deploying RAG architectures and integrating structured and unstructured knowledge sources into AI solutions
•Performance & Security: Knowledge of system-level optimisation and security best practices for scalable AI systems
•Business Acumen: Ability to translate business requirements into technical solutions and communicate technical value to diverse stakeholders, including executive audiences
•Flexibility: Willingness to travel and work on customer premises as required
•Education: Degree-level qualification in Computer Science, Informatics, Data Science, Engineering, or a closely related discipline - or equivalent professional experience