Senior AI Data Engineer

Location: Dublin, Ireland; hybrid working

Company

hirify.global delivers technology and transformation solutions for global brands and partners with Microsoft, AWS, Oracle, Red Hat, OutSystems, and Snowflake.

What you will do

• Design and build scalable ETL/ELT and AI pipelines with Databricks, PySpark, Delta Lake, and SQL.
• Develop Lakehouse architectures with Bronze, Silver, and Gold data layers, including Delta Live Tables and Databricks Workflows.
• Develop and deploy production-grade Generative AI, RAG, and multi-agent solutions.
• Support MLOps through model training and inference pipelines with MLflow.
• Implement data quality monitoring, governance, metadata management, and event-driven Azure integrations.
• Collaborate across teams, develop feature stores and AI training datasets, contribute to engineering best practices, and mentor engineers.

Requirements

• Strong experience as a Data Engineer, AI Engineer, Machine Learning Engineer, or in a similar role.
• Hands-on experience building and deploying multi-agent AI workflows, Retrieval Augmented Generation solutions, AI agent frameworks, and Databricks data pipelines.
• Strong Python and SQL skills, with experience in Apache Spark and distributed data processing.
• Experience implementing Generative AI solutions in Databricks Workflows and Jobs.
• Strong knowledge of Databricks Lakehouse architecture and hands-on experience with Delta Lake, Unity Catalog, Databricks Workflows, and MLflow.
• Experience with Azure Service Bus, Azure Functions, and Azure Databricks.
• Understanding of data modelling and Medallion/Lakehouse architecture, plus Git-based version control and CI/CD practices.
• Strong understanding of AI/ML pipelines, including data preparation, feature engineering, and model deployment.
• Excellent English communication skills.

Nice to have

• PyTorch and/or TensorFlow experience.
• Experience with Event Hub, Logic Apps, enterprise-scale AI platforms, or regulated environments such as financial services.
• Experience mentoring engineering teams or leading technical initiatives.
• Advanced LLMOps experience, including prompt tracking, trace logging, and regression benchmarking.

Culture & Benefits

• Hybrid and flexible/remote working options to support work-life balance.
• Quarterly performance-related profit share scheme, pension, private healthcare, life assurance, financial advice, and employee discounts.
• Generous holiday allowance, enhanced maternity/paternity leave, marriage/civil partnership leave, and special leave policies.
• Career progression, mentorship coaching, quarterly career development programmes, educational assistance, and incentivised certifications.
• Wellbeing initiatives include gym discounts, Bike to Work, fitness classes, mindfulness workshops, and an Employee Assistance Programme.
• Equal-opportunity workplace with diversity, inclusion, accessibility, and reasonable-adjustment support.