AI Engineer - Semantic Layer & Agentic AI

Opus Recruitment Solutions Limited; Greater London; On-site; GBP 60,000 - 100,000; Full time

Job summary

Opus Recruitment Solutions Limited seeks an AI Engineer to build the data foundations powering next-gen AI applications, agents and copilots. You will design semantic layers and knowledge graphs, and implement AI-ready data models to support scalable RAG and Agentic AI solutions.

You will collaborate with Data Engineering, create retrieval and reasoning capabilities for AI apps, and contribute to data governance and platform architecture.

Qualifications

• Proficient in Python and SQL with hands-on AI/ML exposure.
• Experience building AI/LLM-powered applications and data models.
• Strong knowledge of semantic modelling and knowledge graphs.

Responsibilities

• Design semantic layers, knowledge graphs and AI-ready data models.
• Build RAG and Agentic AI solutions using modern LLM frameworks.
• Collaborate with Data Engineering to provide business context across datasets.
• Develop scalable retrieval, search and reasoning for AI apps.
• Contribute to AI governance and platform architecture.

Skills

Python

SQL

AI/ML/LLM

Semantic modelling

Knowledge graphs

RAG/Agentic AI

Vector databases

Cloud (AWS/Azure/GCP)

LangChain

Data platforms

Tools

Neo4j

LangChain

LlamaIndex

Databricks

Snowflake

LangGraph

Job description

We're looking for an AI Engineer to help build the data foundations powering the next generation of AI applications, agents and copilots.

Key Responsibilities

• Design and develop semantic layers, knowledge graphs and AI-ready data models
• Build RAG and Agentic AI solutions using modern LLM frameworks
• Work with Data Engineering teams to create business context across complex datasets
• Develop scalable retrieval, search and reasoning capabilities for AI applications
• Contribute to AI governance, data quality and platform architecture

Required Experience

• Strong Python and SQL skills
• Experience with AI/ML, LLMs or GenAI applications
• Knowledge of semantic modelling, knowledge graphs or metadata-driven architectures
• Experience with RAG, vector databases and modern AI frameworks
• Exposure to AWS, Azure or GCP

Desirable

• Neo4j or graph database experience
• LangChain, LangGraph or LlamaIndex
• Databricks, Snowflake or modern data platforms
• Agentic AI and AI platform engineering