Data AI Engineer
Role summary
Seeking an AI Engineer with Databricks expertise to join the AI & Automation Enablement workstream. This role focuses on developing and implementing autonomous AI agents, data quality AI solutions, decision intelligence, advanced analytics, and ML/AI capabilities within the Databricks ecosystem. Responsibilities include leveraging Databricks SQL, Unity Catalog, Databricks Lakehouse, AI/BI Genie, and Agent Bricks. Experience with MLflow for model lifecycle management, GenAI, data quality automation, and integration with Azure and enterprise data sources is crucial. Strong proficiency in Python, PySpark, SQL, and data engineering fundamentals is required.
Please see the required skillset for the AI Engineer (Databricks) role. This role is aligned to the AI & Automation Enablement workstream, including autonomous AI agents, data quality AI, decision intelligence, advanced analytics, ML/AI, Databricks SQL, Unity Catalog, Databricks Lakehouse, AI/BI Genie, and Agent Bricks capabilities.
Required Skillsets: AI Engineer (Databricks)
\* Databricks Lakehouse architecture and implementation
\* Databricks SQL, notebooks, workflows, and job orchestration
\* AI/BI Genie implementation and business-facing conversational analytics
\* Agent Bricks and autonomous AI agent development within Databricks
\* MLflow for model tracking, deployment, and lifecycle management
\* AI/ML model development, validation, and operationalization
\* GenAI and AI agent development using Databricks capabilities
\* Data quality automation, anomaly detection, and intelligent validation
\* Unity Catalog, data governance, lineage, and access control
\* Integration with Azure, APIs, and enterprise data sources
\* Experience building AI-driven recommendations, smart notifications, and decision intelligence workflows
\* Strong Python, PySpark, SQL, and data engineering fundamentals
