Back to SearchPrincipal AI & Data Engineer
Hybrid in The United Kingdom: London
AI Solution Engineering& 6 others
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We are looking for a Principal AI & Data Engineer to join our team in London, UK in a hybrid working mode. In this role, you will design, build and productionize enterprise-grade AI and GenAI solutions on Azure and Databricks platforms. You will develop scalable AI applications, intelligent agents and data-driven solutions powered by large language models and modern AI frameworks. The role requires hands-on expertise in AI data engineering, cloud technologies and GenAI adoption while driving innovation, reliability and scalability across enterprise environments.
Responsibilities
- Develop and evaluate AI, GenAI and Agentic AI solutions using enterprise AI platforms and frameworks
- Build and optimize Retrieval-Augmented Generation (RAG) applications, including embedding strategies, prompt engineering and evaluation processes
- Design, develop and deploy AI agents using frameworks such as LangChain, LangGraph, AutoGen and similar technologies
- Create scalable AI workflows using Databricks, MLflow, Azure AI Foundry and cloud-native services
- Build and maintain robust data pipelines using modern data engineering practices and streaming technologies
- Deploy AI applications and services using Azure OpenAI, Azure AI Foundry, Databricks AI tools and Docker
- Design and execute evaluation frameworks to measure model quality, accuracy, reliability and reproducibility
- Implement CI/CD pipelines, testing frameworks, code quality controls and GitHub-based development processes
- Collaborate with stakeholders to translate business requirements into scalable AI solutions
- Contribute to architecture decisions, technical roadmaps and backlog definition while supporting delivery from prototype to production
Requirements
- Bachelor’s or Master’s degree in Statistics, Mathematics, Econometrics, Computer Science or a related field
- 8+ years of experience delivering data engineering, machine learning or AI solutions in enterprise environments
- Strong AI Data Engineering expertise with experience building production-grade AI and GenAI systems
- Hands-on experience with Azure AI Foundry, Azure cloud services and Databricks AI technologies
- Deep understanding of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) solutions
- Strong experience with MLflow, GenAI evaluation frameworks and model benchmarking methodologies
- Advanced programming skills in Python and SQL with strong knowledge of data modeling and ETL/ELT processes
- Solid understanding of Delta Lake, Delta Live Tables, Unity Catalog, Spark Structured Streaming and large-scale data processing
- Experience with Azure Data Factory (ADF), Qlik Replicate and modern data architecture practices
- Excellent communication, stakeholder management, problem-solving skills and commitment to high-quality delivery
Nice to have
- Experience in commodity trading and supply operations, ideally within the energy sector
- Experience with Microsoft Copilot Studio, Databricks Mosaic AI, Agent Bricks or Genie
- Experience with LangGraph, AutoGen or other agent orchestration frameworks
- Familiarity with enterprise AI governance, security and compliance practices
- Experience leading technical teams, defining technical strategy and mentoring engineers