DevOps Engineer - Azure Databricks & Azure Cloud Operations

What success looks like in this role:

• Design and provision a secure Azure AI Foundry ML architecture for OCR-based billing data extraction, taking models from validation through production deployment to resolve revenue-impacting invoice processing delays. • Build and operate an end-to-end AI pipeline — ingestion, model inference, and REST API integration — Azure Container Apps, API Gateway • Containerized Python/FastAPI microservices with Docker, publish images to Azure Container Registry, and deploy to Azure Container Apps, enabling scalable HTTP-based model serving. • Build CI/CD pipelines (Azure DevOps) automating deployment and version control for ML-enabled infrastructure and application services. • Implement pipeline monitoring and observability (Azure Application Insights, centralized logging) to track model and service performance in production. • Designing and managing environments that combine on-premises infrastructure with cloud services. • Integrating AI-driven automation to streamline tasks like resource provisioning and security enforcement, enhancing efficiency and adaptability. • Researching new technologies related to the development of distributed applications on the Cloud platform

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You will be successful in this role if you have: BE degree with 2+ years relevant experience Experience in DevOps and Cloud Operations. Strong knowledge of Microsoft Azure services. Experience with Azure Databricks (ADB). CI/CD tools such as Azure DevOps, Jenkins, or GitHub Actions. Scripting experience in Python, PowerShell, or Shell scripting. Knowledge of Infrastructure as Code (Terraform, ARM templates, etc.). Experience with monitoring and incident management.

Preferred Skills: Experience supporting data platforms and analytics environments. Knowledge of containers (Docker/Kubernetes). Understanding of cloud security and governance. AI/ML technical writer from the perspective of a perpetual learn Distilled intricate topics into digestible content, catering to both novice learners and seasoned professionals in the field Demystify the intricacies of computer vision, machine learning frameworks, and advanced neural network architectures

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