Principal AI Data Engineer

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Find me a jobWe're looking for a Principal AI Data Engineer to join our team in London, United Kingdom in a hybrid working mode. In this role, you will design and implement advanced AI and GenAI solutions that deliver real business impact. You will work across architecture, engineering and research to build data and AI-enabled platforms, ensuring performance and scalable solutions that accelerate digital transformation for enterprise environments.

Develop and evaluate AI/GenAI/AgenticAI prototypes using tools such as Copilot Studio, AI Foundry, Copilot Analyst Agent, Mosaic AI, Genie, AgentBricks and MLflowBuild and optimize Retrieval-Augmented Generation (RAG) systems including embedding model selection, prompt engineering and traceable evaluationDesign and deploy basic AI agents using frameworks such as LangChain, AutoGen and smolagentsDeploy models and applications leveraging Azure OpenAI, Azure AI Foundry, Databricks Mosaic Gateway and containerization with DockerFollow DevOps best practices including CI/CD pipelines, testing, linting and GitHub workflowsWrite modular reusable Python code using OOP design patterns and frameworks such as Pydantic and PyTorchEmphasize reproducibility, open-source practices and performance tuning in end-to-end deliveryOperate within agile teams, contributing to sprint planning and collaborative reviewsBuild scalable AI workflows and architectures using tools like Databricks, Genie and LangChainLead architectural planning and backlog creation to ensure long-term reliability and maintainabilityBachelor's or Master's degree in Statistics, Mathematics, Econometrics or similar discipline8+ years of experience in data science and AI projectsDeep understanding of large language models (GPT, Llama, Claude, Mistral) and their reasoning capabilitiesStrong experience with Databricks including DLT, Delta Lake and Unity Catalog governanceSolid knowledge of streaming technologies such as Spark Structured Streaming and AutoloaderProficiency in programming with Python, SQL or ScalaExpertise in data modeling, ETL/ELT processes and data architectureGood understanding of DevOps practices including Git standards and CI/CD automationExperience working in Azure cloud environmentsFamiliarity with GenAI evaluation frameworks, benchmarking and testing methodologiesExcellent problem-solving, communication and stakeholder management skillsUnderstanding of enterprise AI governance modelsHands-on experience with Microsoft Copilot, AI Foundry, Databricks MosaicAI and AgentBricksStrong decision-making capabilities and conflict resolution skillsProven ability to identify and mitigate risks in data-centric projectsFamiliarity with commercial operations in trading and supply environments