Senior DevOps Engineer – Azure & Databricks (AI/ML Focus)

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About The Role

We are seeking a Senior DevOps Engineer with expertise in Azure Databricks and cloud-native AI/ML operations. You will be a key contributor to a next-generation AI platform built on Azure Databricks, enabling data scientists and engineers to train, deploy, monitor, and govern ML and GenAI models efficiently. This role blends MLOps best practices, cloud-native architecture, and Databricks expertise to ensure AI models are production-ready, scalable, and compliant with enterprise standards.

Key Responsibilities

• Design, implement, and optimize ML/AI pipelines for training, deployment, monitoring, and governance.
• Leverage Azure Databricks capabilities including MLFlow for experiment tracking and Unity Catalog for data governance.
• Build and maintain CI/CD pipelines as well as automated ModelOps workflows for AI/ML applications.
• Ensure data architecture supports schema evolution, governance, and compliance requirements.
• Operate in a cloud-native Azure environment to deliver robust and scalable ML solutions.

Required Skills & Experience

• Proven experience with Azure Databricks, including MLFlow and Unity Catalog.
• Strong background in DevOps for ML/AI, including CI/CD and pipeline automation.
• Solid understanding of data architecture, schema evolution, and governance principles.
• Experience working in Microsoft Azure or similar cloud environments.
• Hands‑on experience with Infrastructure as Code (IaC) using Terraform.

Nice to Have

• High-level understanding of machine learning and generative AI concepts and workflows.
• Solid knowledge of containerization (Docker) and orchestration (Kubernetes).
• Experience in Python software development and scripting.
• Hands‑on experience with TensorFlow, PyTorch, and Scikit‑learn in a Databricks environment.

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