QA Engineer (Exp-3+ Years)
- Compensation
- ₹600K–₹1M / yr
- Location
- Bengaluru
- Work setup
- Remote
- Seniority
- Not specified
- Employment
- Contract
- Experience
- 3+ years
- Category
- Qa
- Posted
Skills
Must have
- -Solid understanding of software testing concepts, QA methodologies, and SDLC/STLC.
- -Proven experience in manual testing across web and API layers.
- -Strong experience with API testing tools — Postman, Swagger, or similar.
- -Hands-on expertise in SQL including complex queries, joins, and data integrity validation.
- -Practical experience with automation testing using Selenium, Python, Pytest, or Playwright.
- -Hands-on use of AI tools (ChatGPT, GitHub Copilot, Claude, or similar) in a QA workflow.
- -Ability to craft effective prompts to produce structured test plans and BDD scenarios.
- -Exposure to version control systems (Git).
- -Strong analytical, debugging, and documentation skills.
- -Bachelor's degree in Computer Science, Engineering, or a related field.
- -3–4 years of hands-on QA experience across web, API, and backend systems.
- -Demonstrated use of AI tools in a testing workflow — examples or project references preferred.
- -ISTQB Foundation (or higher), Selenium certification, or equivalent QA certification is a plus.
- -Strong communication skills with the ability to articulate quality risks to technical and non-technical stakeholders.
Nice to have
- -Experience with CI/CD pipelines — Jenkins, GitHub Actions, or Azure DevOps.
- -Familiarity with test management tools such as JIRA, TestRail, or Zephyr.
- -Knowledge of performance testing tools like JMeter or Locust.
- -Basic understanding of security testing concepts.
- -Experience with AI-native testing platforms such as Mabl, Testim, or Applitools.
- -Cloud testing experience on AWS or Azure.
- -BDD experience with Cucumber or Gherkin.
- -Basic awareness of testing AI/ML model outputs — hallucination detection, prompt injection risks.
Full description
Compensation: ₹6L – ₹10L • No equity
Job Position- QA Engineer
No of Positions- 2
Experience- 3-4 Years , Organization- Emplay Analytics Inc
Salary (CTC Offered)- 6 LPA-10 LPA
Job Location- Remote / Work from Home
Immediate joiners preferredJob Summary
We are looking for a proactive QA Engineer with 3–4 years of experience and strong hands-on expertise in manual and automation testing. The ideal candidate is detail-oriented, passionate about quality, and experienced in building reliable test strategies for web, API, and backend systems. You will play a key role in ensuring product stability by driving test planning, execution, automation, and release validation — and by actively leveraging AI tools to enhance testing efficiency in a fast-paced agile environment.
Key Responsibilities Test Strategy & Design
-Develop and maintain detailed test plans, test cases, and test scenarios aligned with functional and non-functional requirements.
-Prioritize testing efforts based on risk assessment and business impact.
-Collaborate with stakeholders to ensure complete requirement coverage before testing begins.
-Use AI tools to auto-generate test cases, edge cases, and boundary conditions from user stories and specifications.
API & Backend Testing
-Conduct thorough functional, integration, and regression testing on RESTful APIs using tools like Postman or Swagger.
-Validate backend data accuracy and integrity through well-structured SQL queries including joins and aggregations.
-Identify and document API contract violations and data inconsistencies across environments.
Automation Development
-Design, build, and maintain scalable test automation frameworks using Python, Pytest, or Playwright.
-Embed automated test suites into CI/CD pipelines to enable continuous quality checks.
-Continuously refactor and improve automation scripts to reduce flakiness and maintenance effort.
-Use AI copilot tools to accelerate test script authoring and maintenance.
AI-Augmented Testing
-Actively use AI tools to generate test cases, identify coverage gaps, and speed up exploratory testing.
-Apply AI-driven insights to detect recurring defect patterns and prevent quality regressions across releases.