• 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.
• Solid 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 d