Cleanroom Release Verification Engineer
- Experis
- 5 - 8 years
- Hyderabad
- 5 days ago
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Job Description
Position: Cleanroom Release Verification Engineer Kubernetes / Cloud
Company: Wipro
Job Type: Permanent
Notice Period: Immediate to 30 Days
Job Location: Hyderabad, Bangalore
Experience: 5 - 8 Years
Budget: 19 LPA Max
Job Description:We are seeking an experienced Clean Room Release Verification Engineer to validate end-to-end product upgrades, deployment workflows, and integration flows for a complex, containerized product ecosystem running on Kubernetes (K8s) across cloud environments such as AWS EKS.This role requires strong technical expertise in Kubernetes deployments, Helm charts, automation, and troubleshooting, along with a solid understanding of test methodology. You will also use AI-driven tools (such as Amazon Q or MCP-enabled systems) to accelerate debugging, deployment analysis, and test creation, and participate in security scanning and vulnerability verification of deployment artifacts.
Key Responsibilities:
Product Deployment & Upgrade Verification:
- Perform end-to-end upgrade and deployment validation across multi-service product landscapes using the product documentation.
- Validate Helm chart upgrades, rolling updates, config map changes, secrets, environment variables, and cluster-level modifications.
- Ensure deployments follow defined architecture, performance criteria, and backward-compatibility requirements.
- Verify successful rollback strategies, version compatibility, and system stability after upgrades.
Test Planning & Execution:
- Define and execute E2E product-level test cases related to deployment, scalability, and functional stability.
- Analyze business and technical requirements to develop a comprehensive test plan and customer-specific deployment test scenarios.
- Continuously track and analyze system behavior and key metrics before and after upgrades.
Troubleshooting & Validation:
- Perform root-cause analysis for failed deployments, pod crashes, configuration issues, and resource-related failures.
- Work hands-on with logs, monitoring dashboards, Kubernetes events, and container diagnostics.
- Drive resolution by collaborating with engineering, DevOps, and platform teams.
Automation, Scripting & Test Tools:
- Create shell scripts to automate day-to-day verification tasks, log collection, environment setup, and routine validation.
- Use tools such as Postman, JMeter, and SoapUI to validate APIs and system behavior after deployment.
Security & Compliance:
- Execute basic pre- and post-deployment security scans, vulnerability checks, image checks, and configuration validation.
- Validate remediation of security issues and ensure secure deployment practices.
AI Tools & MCP Exposure:
- Utilize AI-driven tools (e.g., Amazon Q, GitHub Copilot, internal AI assistants) to accelerate:Debugging of deployment issuesAnalysis of logs and cluster statesGeneration of automated test artifactsInterpretation of upgrade impacts
- Work with MCP (Model Context Protocol)-based servers to integrate AI-assisted workflows in troubleshooting and test creation.
Environment & Collaboration:
- Support preparation, maintenance, and verification of test environments, staging setups, and simulators.
- Work collaboratively in Agile teams across Dev, QA, and DevOps functions.
- Report defects, risks, and test coverage using JIRA and X-Ray.
Required Skills:
- 5-8 years of experience as QA or Deployment Verification Engineer.
- Strong understanding of test methodologies, reporting, and automation best practices.
- Hands-on experience withKubernetes deployments on cloud infra (AWS EKS preferred), Helm charts, config maps, secrets, upgrades, helm install/upgrade, kubectl and Kubernetes troubleshooting
- Working knowledge of:JMeter, Postman, SoapUILinux administration and basic IP networkingCI/CD using Jenkins
- Security scanning and vulnerability tools (e.g., trivy, AWS Inspector, or similar)
- Experience writing Shell scripts for automation.
- Strong analytical and communication skills.
- Experience working in Agile environments.
Added Advantage:Exposure to AI tools like Amazon Q for development/testing productivity.Understanding of MCP-based AI servers for context-aware engineering workflows.
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Engineering - Software & QARole Category: Quality Assurance and TestingRole: Quality Assurance and Testing - OtherEmployement Type: Full timeContact Details:
Company: ExperisLocation(s): Hyderabad
Keyskills: Clean Room Testing Docker Deployment Testing Helm Charts Kubernetes CI/CD Pipeline Shell Scripting DevOps Testing JMeter Jenkins Performance Testing Linux Release Validation API Testing Containerized Applications Postman
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