DevOps Engineer –Azure
2 weeks ago
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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