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Ai Qa Jobs (NOW HIRING)

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 ...

Introlligent Inc.

QA

Austin, TX · On-site

$41 - $55.75/hr

AI Test Automation Engineer Location: Cupertino, CA or Austin, TX (Hybrid - Tue/Wed/Thu Onsite ... A solid QA automation background is required. Key Responsibilities * Lead AI quality and ...

Introlligent Inc.

QA

Cupertino, CA · On-site

$51 - $69.50/hr

AI Test Automation Engineer Location: Cupertino, CA or Austin, TX (Hybrid - Tue/Wed/Thu Onsite ... A solid QA automation background is required. Key Responsibilities * Lead AI quality 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 ...

New

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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How much do ai qa jobs pay per hour?

As of Aug 20, 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 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.

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.

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.

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.

How to become an AI QA tester?

To become an AI QA tester, you should have a strong understanding of software testing principles, familiarity with AI and machine learning concepts, and experience with testing tools and scripting languages. Gaining knowledge of AI models, data validation, and quality assurance processes is essential, and certifications in software testing or AI can enhance your qualifications.
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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 40% Full Time, 20% Part Time, and 40% Contract. Highlights an 80% In-person, and 20% Remote job distribution, with an average salary of $83,472 per year, or $40.1 per hour.

Conversational AI QA Lead

Saransh Inc

Irving, TX • On-site

Full-time

Re-posted 2 days ago

Job description

 

Job Description – 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 virtual assistants for banking use cases.
  • Develop and implement a comprehensive QA strategy that aligns with our product roadmap and business goals.
  • Lead, mentor, and grow a high-performing QA team, fostering a culture of continuous improvement and accountability.
  • Establish and enforce quality standards, processes, and best practices for software testing, including automated and manual testing methodologies.
  • Collaborate with product management, engineering, and operations teams to define quality metrics and ensure alignment on product quality goals.
  • Oversee the design and execution of test plans, test cases, and automated test scripts to validate product functionality and performance.
  • Provide regular updates to executive leadership on quality metrics, testing progress, and risk assessments related to product releases.
  • Identify and advocate for quality improvements throughout the product development lifecycle.

Skills Required: 

  • 10+ years of experience in software quality assurance, with at least 5 years in a leadership role.
  • Proven track record of developing and executing QA strategies for complex software products.
  • Deep understanding of software testing methodologies, tools, and best practices.
  • Experience with test automation frameworks and CI/CD pipelines.
  • Strong analytical and problem-solving skills, with the ability to manage multiple priorities in a fast-paced environment.

Kind regards,

Yousuf Ali

Saransh, Inc.,

Delivery Head

5 Independence Way,

Suite # 225 - Princeton, NJ 08540

Cell: 6094299567 || www.saranshinc.com

a Certified Woman & Minority Business Enterprise (WMBE) 

an Inc. 5000 Company - 2020 

a NJFAST 50 Growing Company - 2020
a Tech Serve Alliance Excellence Award Company - 2019