Cloud Engineer-Azure

Cloud Engineer – Azure AI Solutions \& Deployment Position Type: Full\-time Experience Required: 3\+ Years Location: Chennai Department: Cloud Infrastructure and AI Engineering **About the Role** We are seeking an experienced Cloud Engineer with deep expertise in Microsoft Azure and AI application integration. In this role, you will design, deploy, manage, and optimize AI applications on Azure infrastructure, while ensuring seamless integration and resolving complex deployment challenges. You will be instrumental in building scalable, secure, and high\-performance cloud solutions that power our organization's AI\-driven initiatives. This is a critical position for engineers who combine strong Azure infrastructure knowledge with hands\-on experience in deploying, integrating, and troubleshooting AI solutions in production environments. **Key Responsibilities** **Azure Infrastructure Management** · Design, implement, and manage highly available, multi\-region Azure cloud infrastructure solutions · Provision, configure, and optimize Azure resources including virtual machines, storage accounts, networking components, and databases · Manage Azure virtual networks, subnets, network security groups, and implement advanced networking architectures · Implement Infrastructure as Code (IaC) using Azure Resource Manager (ARM) templates, Terraform, and Azure Bicep · Automate infrastructure deployment and management using scripting and automation tools (PowerShell, Azure CLI, Python) · Monitor system performance, resource utilization, and optimize cloud costs through continuous analysis and improvement **AI Application Integration \& Deployment** · Deploy and integrate AI and machine learning applications on Azure platforms including Azure Machine Learning, Cognitive Services, and Azure AI Services · Configure and manage containerized AI applications using Azure Container Registry (ACR) and Azure Kubernetes Service (AKS) · Implement CI/CD pipelines for AI application deployment using Azure DevOps, GitHub Actions, or similar tools · Integrate AI solutions with existing enterprise applications and databases · Configure data pipelines and ETL processes to support AI model training and inference · Manage model lifecycle including versioning, deployment, A/B testing, and canary releases. **Troubleshooting \& Issue Resolution** · Diagnose and resolve complex issues arising from AI application deployments in Azure environments · Analyze deployment failures, performance bottlenecks, and configuration errors with systematic troubleshooting approaches · Implement monitoring and logging solutions using Azure Monitor, Application Insights, and Log Analytics · Resolve integration issues between AI services, APIs, and backend infrastructure · Conduct root cause analysis (RCA) for production incidents and implement preventive measures · Provide Tier 3 technical support and guidance to development and data science teams · Troubleshoot containerization, networking, and security\-related deployment issues **Security \& Compliance** · Implement and enforce security best practices for cloud infrastructure and AI applications · Manage identity and access controls using Azure Active Directory (AAD) and Role\-Based Access Control (RBAC) · Ensure data protection, encryption, and compliance with regulatory requirements (HIPAA, GDPR, DPDP Act where applicable) · Conduct security audits and vulnerability assessments · Implement network security, firewall rules, and DDoS protection mechanisms · Maintain secure credential management and secret handling practices Monitoring, Performance Optimization \& DevOps · Establish comprehensive monitoring, alerting, and logging for AI applications and infrastructure · Optimize application performance, scalability, and cost efficiency · Implement auto\-scaling policies and load balancing solutions · Create and maintain detailed documentation of infrastructure, deployment procedures, and runbooks · Collaborate with development teams to support CI/CD pipeline implementation and optimization · Stay current with Azure service updates and implement new features and improvements · Participate in capacity planning and infrastructure forecasting **Collaboration \& Knowledge Sharing** · Work closely with solution architects, data scientists, data engineers, and development teams · Provide technical guidance on Azure best practices and cloud\-native architecture patterns · Lead knowledge transfer sessions and mentoring for junior team members · Participate in incident management and on\-call support rotations **Required Qualifications** **Experience** · 3\+ years of professional experience as a Cloud Engineer, DevOps Engineer, or similar role with focus on cloud infrastructure management · 2\+ years of hands\-on experience with Microsoft Azure platform and services · 1\+ years of experience deploying, integrating, and troubleshooting AI/ML applications in cloud environments · Proven track record of resolving production issues and managing critical infrastructure **Technical Skills \- Core Competencies** · Azure Services: Deep expertise in virtual machines, virtual networks, App Service, Azure SQL Database, Azure Storage, Azure Functions, and Azure Cognitive Services · AI \& ML Platforms: Hands\-on experience with Azure Machine Learning, Azure AI Services, Azure Synapse Analytics, or similar AI/ML platforms · Containerization \& Orchestration: Proficiency with Docker, Azure Container Registry (ACR), and Azure Kubernetes Service (AKS) · Infrastructure as Code (IaC): Advanced knowledge of ARM templates, Azure Bicep, Terraform, or similar tools · Scripting \& Automation: Strong proficiency in PowerShell, Azure CLI, Python, or Bash for automation and infrastructure provisioning. CI/CD \& DevOps: Experience with Azure DevOps, GitHub Actions, or Jenkins for continuous integration and deployment pipelines · Monitoring \& Diagnostics: Proficiency with Azure Monitor, Application Insights, Log Analytics, and performance troubleshooting tools · Networking: Strong understanding of cloud networking concepts including load balancing, VPNs, and network security groups · Deployment \& Troubleshooting: Proven expertise in diagnosing and resolving complex deployment issues, performance optimization, and integration challenges **Certifications (Preferred)** · Microsoft Certified: Azure Administrator Associate (AZ\-104\) or higher · Microsoft Certified: Azure Solutions Architect Expert (AZ\-305\) · Microsoft Certified: Azure AI Engineer Associate (AZ\-104 AI\-102\) · HashiCorp Certified: Terraform Associate · Kubernetes Application Developer (CKAD) or similar container orchestration certification **Education** · Bachelor's degree in computer science, Information Technology, Engineering, or related field (or equivalent professional experience) **Required Soft Skills** · Problem\-Solving: Exceptional analytical and troubleshooting abilities with a methodical approach to complex technical challenges · Communication: Clear ability to explain technical concepts to both technical and non\-technical stakeholders · Collaboration: Strong team player who works effectively across multiple departments and functions · Attention to Detail: Meticulous approach to infrastructure configuration, security implementation, and documentation · Continuous Learning: Proactive approach to staying updated with rapidly evolving cloud technologies and AI/ML advancements · Time Management: Ability to manage multiple priorities and respond effectively to production incidents · Documentation: Excellent technical writing skills for creating comprehensive documentation and runbooks · Critical Thinking: Ability to analyze complex scenarios and implement scalable, sustainable solutions. **Preferred Qualifications** · Experience with healthcare or regulated industry environments · Familiarity with data protection frameworks (HIPAA, GDPR, DPDP Act) · Knowledge of advanced AI/ML concepts including model deployment, inference optimization, and MLOps · Experience with enterprise data platforms and analytics solutions · Exposure to agile development methodologies and SCRUM practices · Previous experience mentoring junior engineers or leading technical initiatives · Contributions to open\-source projects or technical communities · Experience with additional cloud platforms (AWS, Google Cloud Platform) is a plus but not required. **What We're Looking For** · Technical Excellence: A professional who combines strong Azure infrastructure expertise with practical AI deployment knowledge · Problem\-Solver Mindset: Someone who enjoys diagnosing complex issues and implementing robust, long\-term solutions · Proactive Approach: An engineer who anticipates challenges, implements preventive measures, and continuously optimizes systems · Team Player: Ability to work collaboratively across technical and business teams while also being independent and self\-directed · Passionate Learner: Commitment to staying current with rapidly evolving cloud and AI technologies Job Type: Full\-time Pay: ₹600,000\.00 \- ₹1,200,000\.00 per month Experience: * Cloud Engineer, DevOps Engineer: 3 years (Preferred) Work Location: In person