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Weekday AI (YC W21)
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Quality Assurance Engineer

Quality Assurance Engineer

Weekday AI (YC W21)

5 years

0 Lacs

india

Posted:17 hours ago| Platform:

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Skills Required

engineering test strategy design testing orchestration reliability devops strategies drive analysis tracking reporting regression api aws support microservices kafka data integrity kubernetes deployment automation analyze logging development software tdd code documentation efficiency iam networking monitoring helm containerization docker postman rest jmeter programming scripting java python javascript github gitlab jenkins architecture scalability communication troubleshooting datadog splunk certification

Work Mode

On-site

Job Type

Full Time

Job Description

This role is for one of the Weekday's clients

Min Experience: 5 yearsLocation: IndiaJobType: full-timeWe are seeking an experienced and highly skilled

Quality Assurance (QA) Engineer

to join our dynamic engineering team. The ideal candidate will possess deep expertise in test strategy design, automated and manual testing, and cloud-native architectures, with strong hands-on exposure to distributed systems running on

AWS

, streaming platforms such as

Kafka

, and container orchestration frameworks like

Kubernetes

. In this role, you will be responsible for ensuring the highest standards of product quality, reliability, and performance. You will collaborate closely with cross-functional stakeholders including developers, DevOps engineers, product managers, and solution architects to establish scalable and highly effective testing processes within a fast-paced product environment.

Requirements

Key Responsibilities

Develop, maintain, and execute robust test strategies, comprehensive test plans, and detailed test cases to validate application functionality, performance, and reliability.
Drive end-to-end QA lifecycle activities across requirement analysis, test design, environment readiness, execution, defect tracking, and test reporting.
Build and optimize automated testing frameworks for functional, regression, API, and performance testing to ensure faster and more efficient release cycles.
Work extensively with AWS cloud environments to support the testing of distributed systems, microservices, and serverless architectures.
Validate large-scale event streaming models on Kafka, ensuring message reliability, data integrity, throughput, and high performance across producer-consumer workflows.
Manage test environments deployed in Kubernetes clusters, including creating and executing test scenarios for containerized microservices, rolling updates, and deployment automation.
Analyze production issues, identify root causes, and contribute to ongoing improvements in observability, logging, and system resilience.
Collaborate closely with development and DevOps teams to integrate testing into CI/CD pipelines and improve release speed and deployment confidence.
Implement best practices in software quality discipline, including TDD/BDD methodologies, code quality standards, and comprehensive test documentation.
Continuously explore new automation tools, testing technologies, and best-in-class QA methodologies to enhance team productivity and efficiency.
Mentor junior QA engineers and contribute to building a culture of quality across engineering and product teams.

Required Skills & Qualifications

5-10 years of hands-on experience in Quality Assurance within a fast-paced product development environment.
Strong expertise in AWS services (EC2, S3, Lambda, RDS, EKS, CloudWatch, IAM, networking fundamentals).
Practical experience working with Kafka clusters, topics, partitions, schema registries, performance testing of event-driven applications, and Kafka monitoring tools.
Solid understanding and working knowledge of Kubernetes, Helm charts, containerization (Docker), and cloud-native deployment environments.
Proven experience designing and implementing API and microservices testing frameworks with tools such as Postman, REST Assured, JMeter, Karate, or equivalent.
Strong programming or scripting skills in languages such as Java, Python, JavaScript, or Shell.
Experience integrating automated tests into CI/CD pipelines using GitHub, GitLab, Jenkins, ArgoCD, or similar.
Strong understanding of distributed system architecture, performance bottlenecks, scalability, and reliability testing.
Excellent communication, analytical thinking, troubleshooting abilities, and a strong ownership mindset.

Preferred Qualifications

Experience with performance testing tools and practices for streaming architectures.
Exposure to monitoring and observability tools like Prometheus, Grafana, ELK, Datadog, or Splunk.
Certification in AWS, Kubernetes, or relevant automation frameworks is a plus

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Quality Assurance Engineer