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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Azure Cloud Architect - AI/ML & Data Services - **Company:** MOONITSOLUTIONS INC - **Location:** Niles, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Microsoft Azure, Cloud Computing, Cloud Engineering, Cyber Security, Continuous Integration, Information Engineering, DevOps, Github, Identity and Access Management, Machine Learning, Role-Based Access Control, Azure Active Directory, Azure Machine Learning, Azure Data Lake, Data Streaming, Azure Data Factory, Large Language Models, Snowflake, Multi-Cloud, HybridCloud, Kubernetes, Bicep, Azure AKS, Data Management, Machine Learning Operations, Data Lakehouse, Terraform, Stream Processing, Azure Synapse Analytics, Stream Analytics, Databricks - **Published:** June 24, 2026 - **Apply:** https://www.dice.com/job-detail/ff84aae1-d3d0-4ecb-81be-e15ba75b56ff ## About the Role * 8+ years of experience in cloud architecture and engineering, with at least 5 years focused on Microsoft Azure. * Proven experience architecting and deploying AI/ML solutions on Azure at scale. * Deep hands-on expertise with Azure ML, Azure OpenAI, Azure Databricks, Synapse Analytics, Data Factory, and Azure Kubernetes Service (AKS). * Strong proficiency in infrastructure-as-code using Terraform, Bicep, or ARM templates. * Solid understanding of MLOps, DevOps, and CI/CD pipelines (Azure DevOps, GitHub Actions). * Experience with cloud networking, security architecture, identity management (Entra ID / AAD), and compliance frameworks on Azure. * Excellent communication skills with the ability to translate technical concepts for non-technical stakeholders. * Microsoft Azure certifications (e.g., Azure Solutions Architect Expert - AZ-305, Azure AI Engineer - AI-102)., * Experience with Azure AI Foundry, Prompt Flow, or LLM orchestration frameworks (LangChain, Semantic Kernel). * Familiarity with multi-cloud or hybrid cloud architectures (Azure Arc). * Background in data mesh, data lakehouse, or modern data architecture patterns. * Experience with real-time data streaming using Azure Event Hubs or Azure Stream Analytics. * Prior experience in a consulting, pre-sales, or solutions architecture capacity. * Knowledge of responsible AI practices and AI governance frameworks. ## Description * Architect, design, and implement end-to-end Azure cloud solutions with a focus on AI/ML workloads, data engineering pipelines, and platform infrastructure. * Lead the adoption and integration of Azure AI/ML services including Azure Machine Learning, Azure OpenAI Service, Cognitive Services, and Snowflake. * Define and enforce cloud architecture standards, patterns, and best practices across development teams. * Design secure, scalable data platforms using Azure Synapse Analytics, Azure Data Factory, Azure Data Lake Storage, and related services. * Collaborate with data scientists and ML engineers to operationalize ML models through MLOps practices (CI/CD for models, monitoring, retraining pipelines). * Drive infrastructure-as-code (IaC) adoption using Terraform, Bicep, or ARM templates. * Conduct architecture reviews, cloud readiness assessments, and provide technical guidance on migrating on-premises workloads to Azure. * Ensure compliance with security, governance, and cost management requirements (Azure Policy, RBAC, Defender for Cloud, FinOps). * Mentor and upskill engineering teams on Azure best practices and AI/ML service capabilities. * Engage with stakeholders to present architecture proposals, roadmaps, and technical recommendations. ## Related Videos - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Back(end) to the Future: Embracing the continuous Evolution of Infrastructure and Code](https://www.wearedevelopers.com/videos/440-back-end-to-the-future-embracing-the-continuous-evolution-of-infrastructure-and-code) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [DevOps Maturity Check – a way to balance autonomy and alignment](https://www.wearedevelopers.com/videos/58-devops-maturity-check-a-way-to-balance-autonomy-and-alignment) - [Reference Architecture of AI in the Cloud](https://www.wearedevelopers.com/videos/1613-reference-architecture-of-ai-in-the-cloud) ## Related Articles - 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Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud)