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Ai Quality Assurance Jobs (NOW HIRING)

Keypixel Software Solutions

AI QA Engineer

Denver, CO · On-site

AI QA EngineerIntroduction The AI QA Engineer will play a crucial role in ensuring the quality and reliability of AI systems and applications within our organization. This individual will be ...

New

Saransh Inc

Conversational AI QA Lead

Irving, TX · On-site

- Conversational AI QA Lead - chatbots Locations: Irving/Dallas, Texas FULL TIME Day to Day job Duties: * Develop and implement conversational AI solutions: Design, build, and deploy chatbots and ...

American Society for Quality

$110 - $170/hr

About You You are an AI QA Engineer passionate about transforming software quality through AI-powered testing and intelligent automation. You thrive in innovative environments where you can combine Q ...

Infosys

AI Quality Assurance Consultant

Jersey City, NJ · On-site

$82K - $126K/yr

... software quality standards • Develop user training programs, documentation, and support ... We do it by enabling the enterprise with an AI-powered core that helps prioritize the execution of ...

Aktios Spain

AI QA Engineer

Aurora, CO · On-site

$70 - $90/hr

Buscamos incorporar un/a AI QA Engineer para garantizar la calidad y fiabilidad de sistemas impulsados por Inteligencia Artificial y Machine Learning, incluyendo aplicaciones basadas en LLMs ...

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Ai Quality Assurance information

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How much do ai quality assurance jobs pay per hour?

As of Aug 23, 2026, the average hourly pay for ai quality assurance in the United States is $44.87, according to ZipRecruiter salary data. Most workers in this role earn between $36.54 and $54.57 per hour, depending on experience, location, and employer.

What is AI Quality Assurance?

AI Quality Assurance (AI QA) refers to the processes and practices used to ensure that artificial intelligence systems function accurately, reliably, and ethically. Professionals in this field test AI models for performance, fairness, and compliance with industry standards. They identify bugs, monitor for unintended biases, and verify that AI outputs meet requirements before deployment. AI QA helps build trust in AI technologies by ensuring they deliver consistent and expected results.

How does an AI Quality Assurance professional typically collaborate with data scientists and engineers during the model development lifecycle?

AI Quality Assurance professionals work closely with data scientists and engineers to ensure that models meet performance, reliability, and ethical standards. This collaboration often involves reviewing model requirements, designing and executing test cases, and providing feedback on issues such as data bias or edge-case failures. Frequent communication and teamwork are essential, especially when troubleshooting unexpected results or implementing improvements. By actively participating in development sprints and review meetings, AI QA professionals help maintain high standards and foster a culture of continuous improvement.

What are the key skills and qualifications needed to thrive as an AI Quality Assurance specialist, and why are they important?

To thrive as an AI Quality Assurance specialist, you need a solid background in software testing, machine learning concepts, and programming, often supported by a degree in computer science or a related field. Familiarity with QA automation tools, version control systems like Git, and AI testing frameworks is crucial for effective performance. Strong analytical thinking, attention to detail, and clear communication are valuable soft skills that elevate performance in this role. These skills ensure the reliability, accuracy, and continual improvement of AI systems, directly impacting product quality and user trust.

What is the difference between Ai Quality Assurance vs Data Analyst?

AspectAi Quality AssuranceData Analyst
Required CredentialsCertifications in AI, QA, or software testingDegree in Data Science, Statistics, or related field
Work EnvironmentTech companies, AI development teamsBusiness, finance, marketing sectors
Industry UsageAI product testing, model validationData interpretation, reporting
Common Search IntentUnderstanding QA roles in AIAnalyzing data for insights

While both roles involve working with data and technology, Ai Quality Assurance focuses on testing and validating AI systems to ensure accuracy and reliability. Data Analysts interpret data to inform business decisions. The roles often overlap in tech environments but serve different purposes within the AI and data ecosystem.

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Ai Quality Assurance jobs near you
Infographic showing various Ai Quality Assurance job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 13% Part Time, 4% Contract, and 1% Nights. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $93,338 per year, or $44.9 per hour.

AI QA Engineer

Keypixel Software Solutions

Denver, CO • On-site

Other

Posted 3 days ago

New

Job description

AI QA EngineerIntroduction

The AI QA Engineer will play a crucial role in ensuring the quality and reliability of AI systems and applications within our organization. This individual will be responsible for designing and implementing test automation strategies to validate AI algorithms, models, and systems.

Responsibilities
  • Develop and execute test plans, test cases, and test scripts for AI algorithms and models
  • Implement automated testing frameworks for AI applications
  • Collaborate with data scientists and developers to understand AI algorithms and models
  • Identify and report bugs, issues, and defects in AI systems
  • Conduct performance testing and scalability testing for AI applications
  • Ensure compliance with quality standards and regulatory requirements
  • Provide technical expertise and guidance on QA best practices for AI projects
  • Continuously improve testing processes and methodologies for AI systems
RequirementsRequired Skills
  • Experience in Test Automation
  • Knowledge of AI/GenAI & LLM Testing
  • Experience in AI QA Strategy & Quality Governance
  • Proficiency in Python & SQL
  • Experience in API Testing
  • Familiarity with Cloud Applications
  • Minimum of 10 years in QA/Quality Engineering
Preferred Skills
  • Experience with CI/CD pipelines for AI applications
  • Knowledge of Machine Learning and Deep Learning concepts
  • Certifications in QA or AI-related fields
  • Experience in working with large-scale AI projects

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