Quality Engineer

Position Summary

We are looking for an experienced Quality Engineer with strong test automation and Azure DevOps skills to design, develop, and maintain automated test solutions for cloud infrastructure and application deployment use cases. The primary objective of this role is to transform existing manually executed DevOps deployment test cases into reliable, reusable, and scalable automated test suites.

The Quality Engineer will validate Azure cloud environment deployments, Azure DevOps YAML pipelines, PowerShell scripts, shell scripts, infrastructure configurations, application deployments, database deployments, containerized workloads, and High Availability scenarios. The candidate will work closely with DevOps, Development, Architecture, and Product teams to ensure that deployment solutions are functionally correct, repeatable, secure, and production ready.

Clinisys' AI Philosophy Building an AI‑first organisation is central to Clinisys’ purpose and the impact we deliver. As a global provider of intelligent diagnostic informatics solutions, we build AI‑enabled, cloud‑based platforms to enhance diagnostic workflows across healthcare, life sciences, and public health. By applying intelligent technology thoughtfully and responsibly, we help laboratories and testing environments operate more effectively, generate meaningful insights at scale, and ultimately support healthier and safer communities.

Operating across more than 42 countries, Clinisys expects all colleagues—regardless of role or function—to work confidently with AI‑enabled tools, apply digital and analytical thinking, and continuously adapt as technologies evolve. We must drive an AI-first sense of purpose and urgency.

Job Responsibilities

• Design, develop, and maintain automated test frameworks for deployment validation.
• Convert manual DevOps deployment test cases into automated test suites.
• Build and integrate automated tests into Azure DevOps YAML pipelines.
• Automate validation of Azure cloud environments and deployed infrastructure.
• Verify application deployments to Azure Virtual Machines.
• Validate Oracle Database deployments and application-to-database connectivity.
• Automate testing of Azure Container App deployments, configuration, and health checks.
• Develop automated tests for PowerShell and Shell scripts used in deployment automation.
• Validate deployment scenarios including upgrades, rollbacks, failovers, and disaster recovery.
• Test High Availability (HA) deployments and recovery scenarios.
• Analyze deployment logs, troubleshoot failures, and identify root causes.
• Collaborate with DevOps, Development, CloudOps, and Product teams to improve deployment quality.
• Maintain automation frameworks, testing standards, and technical documentation. Skillset Requirements 4+ years of experience in Quality Engineering, Test Automation, DevOps QA, or related roles. Strong experience with Azure DevOps Services and YAML pipelines. Hands-on experience in automation testing and framework development. Strong PowerShell scripting skills. Experience with Linux/Unix Shell scripting. Experience validating CI/CD pipelines and deployment automation. Strong knowledge of Microsoft Azure services and cloud infrastructure. Experience testing: Azure Virtual Machines Azure Container Apps Azure Networking Application Gateway and Load Balancers Storage Accounts and Key Vaults Azure Monitoring solutions Experience with Oracle database deployment and validation. Understanding of High Availability, failover, and disaster recovery architectures. Experience with Git-based source control and release management. Strong troubleshooting, analytical, and problem-solving skills. Knowledge of Infrastructure as Code validation (Bicep, ARM, Terraform is an advantage). Experience with Python, Pester, Robot Framework, or similar automation tools is preferred. AI & Modern Engineering Skills Candidates should demonstrate: Experience using GitHub Copilot, Microsoft Copilot, or similar AI-assisted development tools. Ability to generate and maintain test automation scripts using AI-assisted technologies. Experience leveraging AI to improve test coverage, automation productivity, and defect analysis. Ability to convert deployment requirements, YAML pipelines, PowerShell scripts, and infrastructure definitions into automated test cases. Experience using AI to analyze deployment logs and identify failures. Understanding of Agentic AI concepts and automated validation workflows. Exposure to Azure AI, OpenAI, or MCP-based solutions is desirable. Strong analytical thinking, collaboration, and continuous learning mindset. Educational Requirements
• UG: B. Tech / B.E.
• Any Specialization, Computers, Electronics/Telecommunication
• PG: MS/ M.Sc . (Science) – Any Specialization, M.Tech – Any Specialization, MCA – Computers