What are the responsibilities and job description for the Cloud Architect position at Quinnox?
Quinnox is a global IT services organization headquartered in Chicago, USA with presence in Europe, Middle East and India.
We are an Agile, Midsize CMMI Level 5, ISO 9001:2008 and ISO 27001:2013 certified organization, working with Fortune 500 clients and have successfully executed projects in over 40 countries across the globe.
Quinnox is led by senior and seasoned professionals, in both business and technology, who have held key executive leadership positions in major banks, consulting groups, and technology products companies. All of us are focused on only one mission—accelerating success for our clients and employees
Role- Azure Cloud Architect
Location- Niles, IL (hybrid 2-3 days onsite)
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.
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).
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 interested in applying for this role, please share your updated resume to dipas@quinnox.com