QA Engineer — AI Testing Skills

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.

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 such as 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 Dev Ops 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.
• Mentor 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, Git Hub 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, Git Hub Actions, or Azure Dev Ops.
• Familiarity with test management tools such as JIRA, Test Rail, 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.

• 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.