Lead GenAI & Data Engineer (Hybrid London)

Tatton Recruitment; Greater London; Hybrid; GBP 120,000 - 180,000; Full time

Job summary

Certain Advantage in London is seeking a Principal AI Data Engineer for an initial contract through year-end, with a hybrid setup requiring three days on site in London. You will lead the development of AI and GenAI prototypes, focusing on RAG, agent frameworks, and production-ready GenAI applications for commercial teams in Trading & Supply.

The role emphasizes Databricks, Azure OpenAI, and large language models, with a strong emphasis on scalable data architectures and DevOps practices.

Qualifications

• Strong experience with Databricks ecosystem and ML tooling.
• Deep knowledge of Large Language Models (GPT, Llama, Claude, Mistral).
• Experience deploying GenAI, RAG and Agentic AI in enterprise settings.

Responsibilities

• Develop AI/GenAI prototypes using Azure AI Foundry and Databricks Mosaic AI.
• Build and evaluate RAG solutions via prompt engineering and embeddings.
• Design AI agents using LangChain, LangGraph, AutoGen.
• Deliver production GenAI apps for Trading & Supply teams.
• Create scalable AI workflows on Databricks leveraging Mosaic AI and MLflow.
• Apply DevOps practices with CI/CD, GitHub workflows and automated tests.
• Develop evaluation frameworks to benchmark GenAI performance.

Skills

Python

SQL

Scala

GenAI concepts

Tools

Databricks

MLflow

Delta Lake

Unity Catalog

DLT

Azure OpenAI

Azure Data Factory

Qlik Replicate

Spark Structured Streaming

Autoloader

LangChain

LangGraph

AutoGen

Job description

Certain Advantage in London is seeking a Principal AI Data Engineer for an initial contract through year-end, with a hybrid setup requiring three days on site in London. You will lead the development of AI and GenAI prototypes, focusing on RAG, agent frameworks, and production-ready GenAI applications for commercial teams in Trading & Supply.

The role emphasizes Databricks, Azure OpenAI, and large language models, with a strong emphasis on scalable data architectures and DevOps practices.