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Tata Consultancy Services Limited
Azure EngineerTata Consultancy Services Limited • Toronto, ON, Canada
Azure Engineer

Azure Engineer

Tata Consultancy Services Limited • Toronto, ON, Canada
Il y a 25 jours
Type de contrat
  • Temps plein
Description de poste

TataConsultancy Services (TCS) is an equal opportunity employer, and embraces diversity in race, nationality, ethnicity, gender, age, physical ability, neurodiversity, and sexual orientation, to create a workforce that reflects the societies we operate in. Our continued commitment to Culture and Diversity is reflected in our people stories across our workforce and implemented through equitable workplace policies and processes.

Skills and Responsibilities

  • Understanding on Cosmos DB Technical Skills Azure
  • Strong experience with Microsoft Azure
  • Expertise in Azure AI / ML services
  • Proficiency in Python (TensorFlow, PyTorch, Scikit-learn preferred)
  • Hands‑on experience with REST APIs and microservices
  • Knowledge of SQL and NoSQL data stores (Azure SQL, Cosmos DB)
  • Azure AI Engineer Associate Certified (AI-102)
  • Good to have: Networking & Connectivity Design and manage Azure networking components: Virtual Networks (VNet), Subnets
  • Network Security Groups (NSG), Azure Load Balancer, Application Gateway, Azure Front Door
  • Troubleshoot network performance and connectivity issues: Security, Identity & Compliance
  • Collaboration & Support – work closely with application teams, security teams, and architects
  • Provide L2/L3 production support for Azure environments
  • Participate in architecture reviews and cloud migration initiatives
  • Document architecture, procedures, and operational runbooks
  • Azure: collaborate with data scientists, data engineers, developers, and business stakeholders
  • Design and implement AI/ML solutions using Azure AI services such as Azure Open AI, Azure Machine Learning
  • Azure Cognitive Services (Vision, Language, Speech, Decision)
  • Develop and deploy ML models using Python, R, or .NET; build end‑to‑end ML pipelines including data ingestion, training, evaluation, deployment, and monitoring
  • Architect cloud‑native AI solutions leveraging: Azure ML Workspaces, Azure Functions, Azure App Services
  • Ensure scalability, resiliency, performance, and cost optimization
  • Implement Azure security best practices: Managed Identities, Key Vault, Role‑Based Access Control (RBAC); support production issues and continuous improvement initiatives
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