DevOps Engineer –Azure

3 weeks ago

Hyderabad, India QualiZeal Full time

Position: DevOps Engineer – Azure (AI Platforms) Location: Hyderabad, India (Full-time work from office) Experience Required: 5+ Years (with a strong focus on Azure DevOps and cloud-native solutions) Employment Type: Full-Time Role Overview We are looking for an experienced DevOps Engineer with strong expertise in Microsoft Azure technologies to join our AI Center of Excellence (AICoE). You will play a key role in supporting the deployment, scaling, and operational excellence of QMentisAI, QualiZeal’s enterprise-grade Generative AI platform for quality engineering, and NexaAI, QualiZeal’s service offering for developing GenAI-based solutions. The ideal candidate should have hands-on experience in Azure DevOps, CI/CD pipeline creation, Infrastructure-as-Code (IaC), and strong familiarity with containerized and microservice-based architecture. Key Responsibilities • Azure DevOps & Automation o Design, build, and maintain CI/CD pipelines using Azure DevOps. o Automate infrastructure provisioning using Terraform, ARM templates, or Bicep. o Manage Azure App Services, Functions, AKS (Kubernetes), and Container Instances. • Cloud Infrastructure & Monitoring o Implement secure, scalable, and reliable Azure cloud environments. o Configure monitoring, logging, and alerting using Azure Monitor, Log Analytics, and Application Insights. o Optimize cloud costs, manage resource utilization, and ensure high availability. • Collaboration & Delivery o Work closely with AI Architects, Developers, and MLOps teams to enable smooth deployments for QMentisAI and NexaAI. o Drive infrastructure-as-code and continuous delivery best practices across AICoE. o Contribute to release automation, testing, and rollback strategies. Required Skills & Qualifications • Technical Expertise o 5+ years of experience in DevOps and the Azure ecosystem. o Strong knowledge of Azure DevOps, GitHub Actions, YAML pipelines, Docker, and Kubernetes. o Familiarity with Terraform, ARM/Bicep, and Helm for infrastructure management. o Experience in monitoring, security, and compliance setup on Azure. o Working experience with REST APIs and microservice architectures. • Professional Attributes o Proactive problem-solver with a focus on automation and reliability. o Excellent communication skills and ability to work in Agile environments. o Strong ownership mindset to support 24/7 uptime for AI platforms. Preferred Qualifications • Exposure to LLM/GenAI pipelines and AI-based workflow automation. • Familiarity with MLOps concepts (model versioning, deployment, monitoring). • Knowledge of security practices like IAM, VNETs, and Key Vault integration.

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