GraphRAG AI Engineer - Knowledge Graph & LLM Expert

Aubay UK

Greater London

Hybrid

GBP 80,000 - 120,000

Full time

37 hours ago

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Job summary

Aubay UK is seeking an experienced AI Engineer with deep expertise in GraphRAG, knowledge graphs and modern AI engineering to join a high-profile Trading & Supply Emerging Technology initiative. This 6‑month contract inside IR35 focuses on researching, prototyping and scaling advanced AI capabilities that combine LLMs, graph-based retrieval, semantic technologies and agentic AI.

The role collaborates with front-office users to validate hypotheses, identify high-value opportunities and build

Qualifications

Strong hands-on experience designing and delivering GraphRAG solutions in enterprise.
Experience with Azure AI Foundry (or equivalent AI platforms), LangChain and/or LangGraph.
Practical expertise in knowledge graph design, graph schemas, ontologies, entities, relationships and traversal patterns.
Experience combining knowledge graphs with LLMs, RAG architectures and semantic/vector retrieval.
Experience with graph databases such as Neo4j or equivalent technologies.
Strong AI engineering and software development experience using modern programming frameworks and cloud-native architectures.
Experience building scalable solutions using LLMs, AI agents and advanced AI frameworks.
Strong understanding of semantic modelling, GraphQL and graph-based architectures.
Experience supporting or building technology for front-office trading teams.
Practical understanding of how trading decisions are informed by market data, analytics, positions, forecasts and qualitative information.
Experience evolving experimental concepts into scalable production-ready solutions.
Strong understanding of APIs, cloud platforms, enterprise integration, data engineering and

Responsibilities

Design and build GraphRAG and knowledge graph-based AI solutions.
Create graph data models, ontologies and semantic representations for complex business domains.
Develop retrieval and reasoning approaches combining graph traversal, vector search and LLM capabilities.
Partner directly with front-office users to understand workflows, challenges and decisionmaking processes.
Research and evaluate emerging AI technologies and techniques.
Rapidly prototype innovative solutions and assess commercial value.
Build solutions with scalability, maintainability and production adoption in mind.
Translate complex business and trading concepts into AI-ready technical models.
Integrate AI solutions using APIs, GraphQL and enterprise platforms.
Contribute to AI architecture, strategy, governance and responsible deployment practices.
Support evaluation, monitoring and guardrails for AI-enabled capabilities.
Focus on a small number of strategic priorities to maximise business impact.