Deep AI/Agentic Engineer

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 & vector-based systems, embeddings, structured reasoning, and semantic workflows.

• Ontology & knowledge modelling literacy, enabling more precise reasoning and data alignment.

• Integrations & 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.