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. Collaborate with data scientists and ML engineers to operationalize ML models.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
Role :Azure Cloud Architect – AI/ML & Data Services
Hybrid – 2-3 days in Niles, IL ( open for relocation)
C2C Contract
Only US Citizen and Gren Card holder accepted
Key Responsibilities
- 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.
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Required Qualifications
- 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).
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Preferred Qualifications
- 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.
If your profile matches , please do share a copy of your resume to gunjan.t@makonissoft.com at an earliest .
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