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Production AI agent and compound AI system engineering using Databricks Mosaic AI: Vector Search RAG, Agent Framework, MLflow evaluation, and tool calling.

Real-time and batch ML model monitoring: detect feature drift, target drift, data quality anomalies, and performance decay without ground truth using Evidently and NannyML.

Production enterprise Retrieval-Augmented Generation (RAG) with Azure AI Search and Azure OpenAI: hybrid search, semantic reranking, document cracking, and Entra ID security.

Comprehensive ML FinOps and GPU cost optimization: Spot instance automation, scale-to-zero autoscaling, INT8/FP8 model quantization, and fractional GPU resource sharing.

Enterprise MLOps consulting on AWS SageMaker, Google Vertex AI, and Azure ML: automated training pipelines, real-time endpoints, model monitoring, and cloud cost governance.

Expert data pipeline orchestration with Apache Airflow, Dagster, and Prefect: automated DAGs, dbt Cosmos integration, self-healing retries, and monitoring.