Our client are a private equity backed firm who are looking for a deep AI/Agentic Engineer to lead the design and delivery of the organisations complex AI-native engagements, from agentic systems to semantic layers. Pair hands-on technical leadership with client trust, shaping both enterprise outcomes and the firm''s long-term engineering capability.Responsibilities:You will design and build production-grade AI systems across:LLM applications using modern orchestration patterns, prompt frameworks, and evaluation loops.Multi-agent architectures, including planning, delegation, safety constraints, and monitoring.Retrieval andamp; vector-based systems, embeddings, structured reasoning, and semantic workflows.Ontology andamp; knowledge modelling literacy, enabling more precise reasoning and data alignment.Integrations andamp; automation, including API workflows, tools, and enterprise connectors.Skills:6-8 years in Software/application engineering, AI engineering, or applied data engineering.Strong experience with LLMs, embeddings, RAG, retrieval stacks, and vector stores.Hands-on experience in multi-agent systems, agent orchestration, or MCP-like tool patterns.Proficiency in Python, including ability to build production-grade workflows.Experience with at least one cloud AI ecosystem (Azure/OpenAI, GCP/Vertex, Anthropic, AWS etc.).Familiarity with semantic modelling, ontologies, or knowledge graph thinking - literacy required, mastery a bonus. ..... full job details .....