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If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!

Role: Senior Test Automation Engineer

Experience: 3-6 years

Location: Mumbai/Bangalore (Hybrid)

Brief About Role

We are looking for a Senior Test Automation Engineer to join our Quality Engineering (TaaS) team. The ideal candidate should possess strong expertise in modern Quality Engineering practices, UI and API automation, CI/CD integration, and automation framework development. The role requires an engineer who can independently own end-to-end testing activities for enterprise applications while contributing to reusable automation frameworks and AI-powered testing accelerators.

The candidate should be passionate about quality, automation, continuous improvement, and leveraging GenAI to improve testing productivity.

Key Responsibilities

Design, develop, and maintain robust UI and API automation test suites using modern automation frameworks.
Independently own end-to-end testing activities including test planning, test design, automation development, execution, defect management, and reporting.
Develop and maintain reusable automation components, libraries, and utilities to improve productivity.
Automate functional, integration, regression, and end-to-end business workflows.
Build and execute API automation using REST Assured (Java), Requests (Python) or Postman framework.
Develop UI automation using Playwright following framework standards and best practices.
Validate backend data using SQL and perform database verification as part of automated test execution.
Integrate automated test suites into CI/CD pipelines (Jenkins, GitHub Actions, etc.) and implement quality gates.
Participate in code reviews and ensure adherence to automation coding standards and framework guidelines.
Leverage GenAI tools (e.g., ChatGPT, GitHub Copilot, Kiro etc.) to accelerate test case creation, automation development, debugging, and documentation.
Collaborate with developers, business analysts, product owners, and DevOps teams throughout the software development lifecycle.
Participate in sprint planning, requirement analysis, and test strategy discussions.
Analyze automation failures, identify root causes, and implement long-term fixes.
Contribute to the development of reusable TaaS accelerators, automation frameworks, and best practices.
Mentor junior engineers and promote automation-first quality engineering practices.

Must Have Skills

Strong understanding of Software Testing Life Cycle (STLC), SDLC, Agile and Scrum methodologies.
Hands-on experience in designing test scenarios, test cases, and test execution.
Strong expertise in UI automation using Playwright.
Experience building and maintaining scalable, reusable automation frameworks.
Strong experience in API automation using REST Assured (Java) or Python Requests.
Hands-on experience with Postman for API testing and validation.
Strong SQL skills with hands-on experience in database testing and backend data validation.
Experience integrating automation suites with CI/CD pipelines using tools such as Jenkins, GitHub Actions, or similar.
Proficiency with Git and version control best practices.
Experience using GenAI tools such as ChatGPT, GitHub Copilot, Kiro, or similar to accelerate test design, automation development, debugging, test data generation, and documentation.
Strong debugging, root cause analysis, and problem-solving skills.
Ability to independently own end-to-end testing activities with minimal supervision.
Excellent analytical, communication, collaboration, and stakeholder management skills.
Ability to mentor junior team members and promote automation and quality engineering best practices.
Strong attention to detail with a quality-first and automation-first mindset.

Nice To Have Skills

Knowledge of AWS services such as EC2, Lambda, API Gateway, S3, RDS, DynamoDB, CloudWatch, ECS/EKS, and IAM.
Experience testing cloud-native applications deployed on AWS.
Experience in Data Warehouse, ETL, or Data Pipeline testing.
Knowledge of source-to-target data validation, data reconciliation, and data quality testing.
Understanding of AI/ML and Generative AI application testing, including LLMs, chatbots, and RAG-based applications.
Experience with performance testing tools such as JMeter or k6.
Exposure to Docker, Kubernetes, and containerized application testing.
Relevant certifications in Playwright, AWS, Quality Engineering, or Agile are an added advantage.

If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!