Full job descriptionOur Client is building the operating system for a large, traditionally under-digitised UK services industry. Their AI platform automates the repetitive operational admin that eats up the majority of operators’ time: managing communications, compliance, coordination, and scheduling.


We’re already live with pilot customers managing over 14,000 units, with strong early demand as we scale toward revenue in 2026. Backed by experienced founders and investors, we’re building toward a clear goal: the defining AI platform in our category


As the first senior data hire, you’ll architect and scale the systems powering our client’s AI products: from real-time pipelines and analytics infrastructure to vector databases and ML data workflows. You’ll define data architecture, tooling, and engineering standards, working closely with AI and backend engineers, and lay the foundations for the future data te


Duties


*Architect and build scalable data pipelines and infrastructure for AI and product systems Design data ingestion, transformation, and storage architectures
*Build batch and real-time pipelines, plus vector search/retrieval systems for ML workflows
*Own data reliability, security, governance, and observability
*Shape long-term data strategy and mentor the team as we scale


What You’ll Bring


*7+ years in data engineering or backend roles
*Strong Python; experience with distributed data systems
*Relational DB experience (PostgreSQL preferred)
*NoSQLExposure to vector databases (Qdrant, Milvus, pg vector)
*Bonus: Spark/Airflow/Kafka, cloud (GCP/AWS/Azure), AI/ML platform experience, early-stage startup background


Why Join


*Build the data foundations of a category-defining AI company
*Work directly with founders and the core engineering team
*Early-stage ownership, influence, and equity upside