Job description

Agentic AI, generative AI and machine learning systems only work as well as the data underneath them, and this QuantumBlack position owns that layer on client engagements. As technical owner of the data engineering workstream, you design scalable data architectures and lead pipeline development. Production work covers prompt design, retrieval-augmented generation (RAG), embeddings, vector databases and context construction, built with frameworks such as Spark, LangChain, Databricks, Airflow, Dagster and Kedro. MLOps and LLMOps architectures handle model management, observability and automated retraining, supported by CI/CD, Terraform and agent evaluation tools like LangSmith, Opik and Langfuse. Feature engineering workstreams are designed to prepare data for the next generation of models. Security and governance matter throughout, from PII and PHI handling to authentication and RBAC. Data Scientists, Machine Learning Engineers and industry experts work alongside you in Agile teams, and clients range from data owners to C-level executives. Mentoring junior engineers and raising software engineering standards are part of the role. At least 5 years in data engineering with expert Python and SQL is required, with Doha, Dubai and Riyadh as the listed offices.