Senior Data Engineer - GenAI

• Own the end to end ML lifecycle, including data ingestion, feature engineering, training, evaluation, deployment, monitoring, retraining, and rollback
• Design, build, and operate production grade ML pipelines using Azure native services with solid CI/CD and automation practices
• Use Azure Machine Learning and MLflow for experiment tracking, model registry, and governed promotion across Dev/Test/Prod environments
• Design and deploy Generative AI solutions using Azure OpenAI, embeddings, vector search, and RAG pipelines
• Build Agentic AI workflows with multi step reasoning, tool usage, guardrails, observability, reliability, and cost control
• Build scalable data and feature pipelines using Azure Databricks (batch and streaming)
• Build scalable data pipelines for text, documents, logs, and multi-modal data
• Develop RAG pipelines including chunking, embedding, and retrieval workflows
• Design and manage vector search systems (Azure AI Search, Pinecone, etc.)
• Build batch + real-time data ingestion pipelines using Spark and Kafka

• 6 8 years of experience in Data Engineering
• Strong hands-on experience with Python / PySpark / SQL
• Apache Spark , Airflow , Kafka
• Handling unstructured data (JSON, logs, documents, PDFs)
• Experience with cloud platforms ( Azure preferred)
• Exposure to LLM / GenAI pipelines (RAG, embeddings, vector DBs)

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