QA Engineer

RemoteJobsOne; Kentucky; Remote; USD 124,000 - 241,000; Part time

Job summary

RemoteJobsOne is seeking a QA Engineer to contribute high-quality evaluation for a high-volume AI training project. You will assess AI outputs, design comprehensive test cases, and document defects with clear reproduction steps. The role emphasizes meticulous written feedback and collaboration to raise testing standards.

The position is fully remote in the United States with hourly pay and immediate start available for qualified QA professionals with strong manual and automated testing skills.

Qualifications

• Proven QA background in software quality assurance with a focus on both manual and automated testing.
• Skilled in test case design, bug tracking, and regression testing.
• Experience with automation frameworks and test-management tools is essential.
• Experience with human data annotation or AI training support is a plus, not required.
• Excellent written English communication and strong attention to detail are mandatory.
• No formal degree required; practical testing experience takes precedence.

Responsibilities

• Evaluate AI-generated outputs against quality rubrics and criteria.
• Design and assess test cases for functional, regression, and edge cases.
• Review bug reports for reproducibility and accurate severity.
• Document defects with precise reproduction steps and tracking.
• Provide actionable feedback to developers to support rapid resolution.
• Collaborate with teams to improve testing guidelines and standards.

Skills

QA Fundamentals

Manual Testing

Automated Testing

Test Case Design

Bug Tracking

Regression Testing

Analytical Thinking

English Communication

Education

No degree required

Tools

Selenium

Playwright

Cypress

Appium

Postman

Jira

TestRail

Zephyr

BrowserStack

Job description

This is a fully remote position, open to candidates based in United States.

Pay: $90–$175/hr

Role Title: QA Engineer

Role Type: Contractor

Location: Remote

We are engaging QA Engineers to contribute expertise in software quality evaluation for a customer's high-volume project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters. This opportunity is open to specialists with strong professional QA backgrounds. Prior paid experience with human data annotation, RLHF, model output evaluation, or rubric-based grading for AI training is a plus, but not required.

Scope of Work

1. Evaluate and rate AI-generated technical outputs against defined quality criteria and rubrics, identifying answers that may appear correct but are actually inaccurate or incomplete.
2. Design and assess comprehensive test cases for functional, regression, and edge-case scenarios, including negative and boundary tests.
3. Review bug reports and test documentation to ensure issues are reproducible, documentation is complete, and severity is properly assessed.
4. Identify, isolate, and document defects with precise reproduction steps and utilize structured tracking mechanisms.
5. Provide detailed, actionable written feedback and annotations to support efficient resolution by developers without the need for clarification.
6. Collaborate with project teams to refine evaluation guidelines and ensure continuous improvement of testing standards and methodologies.

Preferred Qualifications

1. Proven professional experience as a QA Engineer, SDET, Test Engineer, QA Analyst, or similar role in software quality assurance.
2. Strong command of QA fundamentals, including test case design, bug tracking, regression testing, and both manual and automated testing strategies.
3. Hands-on experience with automation frameworks and test management tools such as Selenium, Playwright, Cypress, Appium, Postman, Jira, TestRail, Zephyr, or BrowserStack (or similar tools).
4. Prior paid human data experience supporting AI training — annotation, labeling, RLHF, AI response evaluation, model evaluation, or rubric-based grading — is a plus.
5. Excellent analytical and problem-solving skills with meticulous attention to detail.
6. Ability to communicate complex findings clearly in written English, providing specific, actionable feedback (B2 level or above).
7. No formal degree required—practical, demonstrable testing experience takes precedence.
8. Reliable internet connection and readiness to begin promptly.