Principal AI Data Engineer - GenAI & Agentic AI

We are looking for an experienced Principal AI Data Engineer to develop and deliver enterprise-ready AI, Generative AI and Agentic AI solutions. You will combine data engineering expertise with practical AI experimentation, taking solutions from prototype to production and supporting adoption by business teams. Working with modern cloud and data platforms, you will design scalable AI workflows, build evaluation frameworks and collaborate with technical and business stakeholders to translate commercial needs into effective solutions. You will also help shape technical direction and contribute to future AI capabilities. Responsibilities Develop, prototype and evaluate AI, Generative AI and Agentic AI solutions for practical use cases and enterprise integration Build and optimize Retrieval-Augmented Generation (RAG) systems, including embedding model selection, prompt engineering and traceable evaluation Design and deploy AI agents using frameworks such as LangChain, AutoGen, smolagents and LangGraph Deliver hands-on GenAI and Agentic AI solutions for commercial teams, taking concepts from prototype through production Build and integrate AI solutions using Databricks capabilities, including Mosaic AI, Genie, MLflow and AgentBricks Deploy models and applications using Azure OpenAI, Azure AI Foundry, Databricks Mosaic Gateway and Docker Manage large-scale text and structured datasets using Databricks infrastructure Design and implement GenAI evaluation and testing frameworks, including benchmarking, reproducibility checks and structured model assessments Contribute to data platform and AI architecture, system planning, structured testing and DevOps practices, including CI/CD and automated testing Develop reusable Python code, collaborate with agile teams and business stakeholders, shape technical direction, manage delivery risks and translate business requirements into practical AI solutions Requirements Bachelor’s or master’s degree, or equivalent qualification, in statistics, mathematics, econometrics or a related discipline 8–12 years of experience working on data science and AI projects Deep understanding of large language model families, including GPT, Llama, Claude and Mistral, and their reasoning capabilities Strong hands-on experience with Databricks, including Delta Live Tables (DLT), Delta Lake concepts and Unity Catalog governance Solid understanding of streaming technologies, including Spark Structured Streaming and Auto Loader Strong programming skills in Python, SQL or Scala, with proficiency in data modeling, ETL/ELT processes and data architecture Experience with data ingestion and replication using Azure Data Factory (ADF) and Qlik Replicate Experience working in Microsoft Azure cloud environments and with Generative AI evaluation frameworks and benchmarking methods Practical experience with Microsoft Copilot, Azure AI Foundry and Databricks AI capabilities, including Mosaic AI, MLflow, AgentBricks and Genie Strong Git practices, analytical and problem-solving skills, stakeholder management, communication and the ability to work independently and collaboratively Nice to have Familiarity with enterprise AI platforms and AI governance models is an advantage Experience supporting commercial business functions is beneficial Ability to establish technical foundations and help lead the development backlog is advantageous