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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 #LI-LS1 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
American multinational technology, cloud application and infrastructure services and consulting corporation
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