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Ai Qa Jobs (NOW HIRING)

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AI Quality Engineer

New York, NY · On-site

$78K - $101K/yr

Identifying Automation Opportunities: Proactively identifying areas within the QA lifecycle and business processes that can be optimized through AI automation. * Excel Automation: Automating data ...

Accord Technologies Inc.

Sr. QA Test Engineer

Alpharetta, GA · On-site

$40.25 - $55/hr

... AI-Aware)  - Load/performance testing for inference endpoints (latency, throughput, concurrency).  - Cost-aware testing (token usage, rate limits, fallbacks).  ...

Giga AI Inc

QA Lead

San Francisco, CA · On-site

$160K - $230K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

Voice AI startup Giga raises $61M Series A * DoorDash and Giga Partnership Giga builds AI agents trusted by the largest B2C companies in the world. Industry leaders like DoorDash trust Giga with ...

Zebra Technologies

AI Quality Analyst

Lincolnshire, IL · On-site

  • Medical

  • PTO

Proven experience in a quality assurance, testing, or data analysis role, preferably within the AI/ML domain. * A deep understanding of the machine learning lifecycle and the common failure modes of ...

RWS Group

Support quality assurance across AI data projects by improving processes, automating quality checks, and monitoring data accuracy. * Develop and maintain testing frameworks, evaluation datasets, and ...

Digipulse Technologies, Inc

AI Engineer

Atlanta, GA · On-site

$69K - $89K/yr

We are looking for an experienced AI Engineer with a background in software engineering, QA, automation testing, or business systems analysis. The ideal candidate should have at least one year of ...

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AI Quality Engineer

New York, NY · On-site

$78K - $101K/yr

AI Agent Test Scenario Creation: Designing robust and relevant test scenarios to validate AI agent ... Integrating QA automation processes with our Master Control Program (MCP) for centralized ...

RWS Group

Support quality assurance across AI data projects by improving processes, automating quality checks, and monitoring data accuracy. * Develop and maintain testing frameworks, evaluation datasets, and ...

Filevine

QA Analyst - LOIS for Word

San Francisco, CA · On-site

$105K - $150K/yr

  • Medical

  • Dental

  • Vision

Filevine is a Legal AI company delivering Legal Operating Intelligence for the future of legal work ... You'll help build and own the QA function: the test strategy, the process, and the automation. You ...

Zebra Technologies

AI Quality Analyst

Lincolnshire, IL

  • Medical

  • PTO

Proven experience in a quality assurance, testing, or data analysis role, preferably within the AI/ML domain. * A deep understanding of the machine learning lifecycle and the common failure modes of ...

Filevine

QA Analyst - LOIS for Word

San Francisco, CA · On-site +1

$105K - $150K/yr

  • Medical

  • Dental

  • Vision

Filevine is a Legal AI company delivering Legal Operating Intelligence for the future of legal work ... You'll help build and own the QA function: the test strategy, the process, and the automation. You ...

Filevine

QA Analyst - LOIS for Word

San Francisco, CA · Remote

$105K - $150K/yr

Filevine is a Legal AI company delivering Legal Operating Intelligence for the future of legal work ... You'll help build and own the QA function: the test strategy, the process, and the automation. You ...

Danaher

Principal AI Quality Engineer

Vista, CA · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The AI Quality Engineer leads quality assurance efforts for AI driven medical device software, overseeing end to end lifecycle development and compliance activities for Artificial intelligence (AI ...

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Ai Qa information

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How much do ai qa jobs pay per hour?

As of Aug 14, 2026, the average hourly pay for ai qa in the United States is $40.13, according to ZipRecruiter salary data. Most workers in this role earn between $28.12 and $49.28 per hour, depending on experience, location, and employer.

What is the difference between Ai Qa vs Data Analyst?

AspectAi QaData Analyst
Required CredentialsTypically certifications in AI, QA, or software testingBachelor's degree in data science, statistics, or related fields
Work EnvironmentTech companies, software development teams, AI-focused projectsBusiness, finance, healthcare, and various industries analyzing data
Employer & Industry UsageTech firms, AI startups, software companiesCorporations across multiple sectors, consulting firms
Common Search & Comparison IntentUnderstanding roles in AI quality assuranceAnalyzing data to inform business decisions

Ai Qa specialists focus on testing and ensuring the quality of AI systems, often requiring knowledge of AI tools and testing protocols. Data Analysts interpret data to generate insights, requiring skills in data visualization and statistical analysis. While both roles work with data and technology, Ai Qa emphasizes quality assurance in AI development, whereas Data Analysts focus on data interpretation for decision-making.

What are the key skills and qualifications needed to thrive as an AI QA?

To thrive as an AI QA specialist, you need strong analytical skills, knowledge of software testing methodologies, and a solid understanding of AI/ML concepts, typically supported by a degree in computer science or a related field. Familiarity with testing frameworks like Selenium or PyTest, version control systems like Git, and tools such as TensorFlow or PyTorch for model validation is often required. Attention to detail, problem-solving abilities, and effective communication set top performers apart in this role. These skills ensure the reliability, fairness, and safety of AI systems, which is critical for delivering trustworthy and high-quality AI solutions.

What is an AI QA?

AI QA (Artificial Intelligence Quality Assurance) professionals are specialists who test and validate machine learning models, AI systems, and related software to ensure they function correctly, reliably, and ethically. They design test cases, evaluate model accuracy, check for biases, and verify compliance with regulatory standards. AI QA experts work closely with data scientists, developers, and product managers to identify issues and improve system performance throughout the AI development lifecycle.

How does an AI QA engineer typically collaborate with data scientists and developers during the model development lifecycle?

AI QA engineers work closely with data scientists and developers throughout the AI model development process. They often participate in sprint planning and daily stand-up meetings to align on testing strategies, clarify requirements, and address potential model issues early. Their responsibilities include designing test cases for model accuracy, fairness, and robustness, as well as validating data pipelines and deployment workflows. Effective communication and a proactive approach are essential, as AI QA engineers help ensure the final model meets quality standards and integrates smoothly into production environments.
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Ai Qa jobs near you
Infographic showing various Ai Qa job openings in the United States as of August 2026, with employment types broken down into 67% Full Time, and 33% Part Time. Highlights an 67% In-person, and 33% Remote job distribution, with an average salary of $83,472 per year, or $40.1 per hour.

AI Quality Engineer

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New York, NY • On-site

$78K - $101K/yr

Contractor

Re-posted 4 days ago

Job description

  • AI Agent Test Scenario Creation: Designing robust and relevant test scenarios to validate AI agent behavior and performance. 

  • PRD Analysis: Analyzing Product Requirement Documents (PRDs) to extract testing requirements and ensure comprehensive test coverage. 

  • Performance Testing: Conducting thorough performance testing of AI systems to identify bottlenecks and ensure scalability. 

  • Agentic Testing: Utilizing agentic coding tools such as Windsurf, Claude Code, and Cursor for advanced automation tasks. 

  • Selenium AI Plugins: Implementing and leveraging AI-powered Selenium plugins, including Healenium and Applitools Eyes, for intelligent visual and functional testing. 

  • QA Automation with MCP Integration: Integrating QA automation processes with our Master Control Program (MCP) for centralized management and execution. 

  • APIs & Integrations: Testing and integrating with REST and SOAP APIs to ensure seamless connectivity between systems. 

  • Process Analysis Workflow Analysis: Analyzing complex business workflows to understand processes and identify pain points. 

  • Identifying Automation Opportunities: Proactively identifying areas within the QA lifecycle and business processes that can be optimized through AI automation. 

  • Excel Automation: Automating data-intensive tasks using Excel automation techniques. 

Required Skills 

  • Minimum 5 years of experience with industry-standard tools such as JIRA, AZDO, Balsamiq, and MS Visio. 

  • Minimum 5 years of experience with automation tools including QTP, WinRunner, Visual Studio, and Selenium. 

  • Minimum 5 years of experience in creating, executing, and managing automation scripts effectively. 

  • Minimum 5 years of experience in utilizing SQL Server, LoadRunner, and JMeter for database management and performance testing. 

  • Minimum 5 years of experience in exhibiting strong understanding and practical experience with Agile and Scrum methodologies. 

  • Minimum 5 years of experience in using version control systems like Git and platforms such as GitHub or GitLab for collaborative development and test management. 

  • Minimum 5 years of experience in exhibiting proficiency in end-to-end defect life cycle management, including logging, tracking, and verifying fixes. 

  • Minimum 5 years of experience in integrating automated tests into Continuous Integration/Continuous Deployment (CI/CD) pipelines using tools like Jenkins or Azure DevOps.