AI​/GenAI & Lakehouse Applications Engineer

Overview

Enable and operationalize production-grade AI, Generative AI, and Lakehouse Applications on Databricks, ensuring governance, scalability, security, and alignment with enterprise data intelligence standards.

• Implement ML lifecycle management using MLflow (experiment tracking, model registry, controlled promotion)
• Design and manage Feature Store assets with proper versioning, reuse, and governance
• Enable Generative AI workloads including prompt management, embeddings, and inference patterns
• Build and deploy Lakehouse Applications for governed AI and analytics consumption
• Implement conversational analytics solutions with secure and semantically consistent access
• Design scalable inference architectures for real-time and batch workloads
• Monitor model performance, feature drift, and data drift
• Ensure AI/GenAI workloads comply with governance policies and access controls

• Integrate AI workflows into CI/CD pipelines and orchestration frameworks
• Collaborate with Platform and Data Ops teams for cost, scalability, and reliability optimization
• Communicate AI risks, limitations, and governance considerations to stakeholders

• Strong hands-on experience with MLflow and ML lifecycle management
• Experience with Feature Store concepts and governed feature engineering
• Exposure to Generative AI concepts (LLMs, embeddings, prompt engineering)
• Experience deploying scalable batch and real-time inference solutions
• Understanding of data governance, access control, and secure AI deployment
• CI/CD and production AI operations experience