Responsibilities :
Develop and maintain scalable AI, data integration, and automation pipelines. Enhance Azure Durable Functions workflows, orchestration, error handling, and performance optimization. Build and support integrations across Snowflake, SAP, Azure services, and enterprise data sources. Productionize AI solutions and resolve platform, pipeline, and data quality issues. Build evaluation and monitoring frameworks for AI/ML workloads. Implement observability, logging, tracing, dashboards, and operational monitoring. Improve automated testing, CI/CD pipelines, authentication, and platform reliability. Collaborate with Data Scientists to operationalize AI models and document intelligence solutions.
Technical and Professional Requirements:
Strong Python development experience with Python 3.x, Pydantic, Pytest, Type Hints, and API development. Experience building cloud-native solutions on Microsoft Azure, including Azure Functions, Durable Functions, Azure OpenAI, Document Intelligence, Cosmos DB, Blob Storage, and Key Vault. Strong data engineering and integration skills with SQL, Snowflake, ETL/ELT pipelines, and enterprise data platforms. Knowledge of CI/CD, Git, GitLab, DevOps practices, observability, monitoring, and logging frameworks. Experience with OpenTelemetry, Application Insights, Grafana, and production monitoring tools. Understanding of secure authentication mechanisms including Managed Identity, OAuth2, and Workload Identity Federation. Exposure to LLM applications, Azure OpenAI, OCR/Document Processing, SAP integrations, MLflow, and Azure ML is preferred.