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We are seeking talented Software QA & Automation Engineers with 5+ years of experience and a passion for delivering high-quality, cloud-native software solutions. In this role, you will design, develop, and execute test automation solutions for cutting-edge applications in the observability domain, leveraging modern testing frameworks, cloud-native technologies, and automation tools. You will collaborate closely with development, product, and operations teams to ensure product quality, reliability, performance, and scalability while driving continuous improvement in test automation and quality engineering practices within an agile environment.
Design, develop, and enhance test automation frameworks and quality engineering solutions for cloud-native observability platforms, ensuring product quality, reliability, and scalability.
Own end-to-end quality validation activities, from test strategy and test design to automation, execution, reporting, and release readiness.
Drive automation-first testing practices across CI/CD pipelines to accelerate delivery, improve release confidence, and reduce manual effort.
Identify, analyze, and track software defects, collaborating closely with engineering teams to ensure timely resolution and continuous quality improvements.
Leverage AI-assisted testing and engineering productivity tools to improve test coverage, accelerate defect discovery, and enhance overall testing effectiveness.
Collaborate with developers, product management, and DevOps teams to embed quality throughout the software development lifecycle while driving continuous improvements in quality engineering practices and Agile delivery processes.
You Have:
Engineering degree with 5+ years of experience in software testing and quality engineering.
Strong experience in test automation development using Java, Python, Go, or similar programming languages, including building scalable automation frameworks.
Hands-on experience testing cloud-native applications deployed on Kubernetes/OpenShift, including microservices-based and distributed systems architectures.
Strong knowledge of API, integration, system, and end-to-end testing using modern automation tools and frameworks.
Experience implementing and maintaining CI/CD-driven test automation using tools such as Jenkins, Git, Helm, and containerized deployment pipelines.
Experience testing data-intensive and event-driven systems involving Kafka, databases, ETL pipelines, and large-scale data processing workflows.
Strong defect management, troubleshooting, test analysis, and Root Cause Analysis (RCA) skills for complex distributed applications. Experience working in Agile/Scrum environments with strong collaboration skills and a quality-first mindset.
Nice to Have
Good understanding of observability and telemetry concepts, including metrics, logs, traces, and validation of monitoring and analytics platforms.
Exposure to AI-assisted testing tools, intelligent automation practices, or AI/ML-driven quality engineering approaches.
Experience working with telecom network management, observability, analytics, or autonomous network solutions.
From live job posts on CoreHRx, updated 6 Nov 2026. Skill figures count posts that list their skills; salary figures only posts that show a salary.
The post does not state the pay. As an estimate, comparable posts on CoreHRx advertise ₹11L – ₹24L a year (typical for IT Jobs in India, 962 posts).
The post asks for 5 Yrs experience.
It is a full time job.
Interview preparation · 60 questions
This guide is for Indian job seekers preparing for Java backend roles, from freshers facing campus and first-job interviews to experienced developers moving into senior positions at product companies and IT services firms. It covers what interviewers ask most in 2025 and 2026 on Java 17 and 21 and Spring Boot 3: OOP, collections, equals and hashCode, streams, exceptions, concurrency and JVM memory, then dependency injection, auto-configuration, REST controllers, validation, JPA and Hibernate, security, microservices and testing. Questions are grouped as easy, medium and hard. Read each answer, compile the code yourself and practise explaining it aloud.
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