QA Engineer — AI Testing Skills

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QA Engineer — AI Testing Skills

Job Position- QA Engineer

Experience- 3-4 Years

Company- Emplay Analytics Inc

Salary( CTC Offered)- As per company standards

Job Location- Remote / Work from Home

Job 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.

• Evaluate and adopt emerging AI-powered and self-healing test tools to improve team productivity and test reliability.
• Craft effective prompts to extract structured test plans, BDD scenarios, and API contract tests from AI assistants.

Agile Collaboration

• Participate actively in sprint ceremonies including planning, stand-ups, reviews, and retrospectives.
• Work alongside developers and DevOps teams to shift quality left and catch issues early in the development cycle.
• Support defect triage, root cause analysis, and pre-release quality sign-off. Mentoring \& Documentation
• Guide junior QA engineers on testing best practices, automation techniques, and AI tool usage.
• Maintain clear and up-to-date documentation including test reports, traceability matrices, and release notes.
• Communicate quality risks clearly to both technical and non-technical stakeholders.

Must-Have Skills

• 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.

Nice-to-Have Skills

• 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.

Qualifications

• 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.

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