AI / GenAI & Lakehouse Applications Engineer

OverviewEnable and operationalize production-grade AI, Generative AI, and Lakehouse Applications on Databricks, ensuring governance, scalability, security, and alignment with enterprise data intelligence standards.ResponsibilitiesImplement ML lifecycle management using MLflow (experiment tracking, model registry, controlled promotion)Design and manage Feature Store assets with proper versioning, reuse, and governanceEnable Generative AI workloads including prompt management, embeddings, and inference patternsBuild and deploy Lakehouse Applications for governed AI and analytics consumptionImplement conversational analytics solutions with secure and semantically consistent accessDesign scalable inference architectures for real-time and batch workloadsMonitor model performance, feature drift, and data driftEnsure AI/GenAI workloads comply with governance policies and access controlsSecondary ResponsibilitiesIntegrate AI workflows into CI/CD pipelines and orchestration frameworksCollaborate with Platform and DataOps teams for cost, scalability, and reliability optimizationCommunicate AI risks, limitations, and governance considerations to stakeholdersRequired Skills & ExperienceStrong hands-on experience with MLflow and ML lifecycle managementExperience with Feature Store concepts and governed feature engineeringExposure to Generative AI concepts (LLMs, embeddings, prompt engineering)Experience deploying scalable batch and real-time inference solutionsUnderstanding of data governance, access control, and secure AI deploymentCI/CD and production AI operations experience#J-18808-Ljbffr