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Generative Ai Testing Jobs in Austin, TX (NOW HIRING)

Deloitte

Lead Generative AI Data Engineer III

Austin, TX

$101K - $133K/yr

Lead the design, development, testing, and deployment of machine learning and artificial ... Manage AI engineering workstreams by assigning work, reviewing deliverables, and driving quality ...

Deloitte

Lead Generative AI Data Engineer III

Austin, TX · On-site

$101K - $133K/yr

Lead the design, development, testing, and deployment of machine learning and artificial ... Manage AI engineering workstreams by assigning work, reviewing deliverables, and driving quality ...

UTIMCO

Data & AI Solutions Engineer

Austin, TX · On-site

$113K - $136K/yr

... generative AI technologies, including using AI-assisted development tools to improve productivity and software delivery. * Familiarity with application security, identity management, testing ...

Aprio

Senior AI Product Associate, IT

Austin, TX · On-site +1

$104K - $160K/yr

Familiarity with generative-AI tools and platforms, including hands-on prompting and testing of AI APIs. * Ability to quickly learn new domains and translate complex workflows into product ...

Aprio

Senior AI Product Associate, IT

Austin, TX · On-site +1

$104K - $160K/yr

Familiarity with generative-AI tools and platforms, including hands-on prompting and testing of AI APIs. * Ability to quickly learn new domains and translate complex workflows into product ...

Addison Group

Senior Full Stack AI Engineer

Austin, TX · On-site

$85 - $95/hr

Design, build, and support AI-powered applications using LLMs, generative AI platforms, and agentic ... Knowledge of CI/CD pipelines, automated testing, and source control best practices. * Strong ...

Addison Group

Senior Full Stack AI Engineer

Austin, TX · Remote

$85 - $95/hr

Design, build, and support AI-powered applications using LLMs, generative AI platforms, and agentic ... Knowledge of CI/CD pipelines, automated testing, and source control best practices. * Strong ...

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All JobsGenerative Ai Testing JobsGenerative Ai Testing Jobs in Austin, TX

Generative Ai Testing information

See Austin, TX salary details

$31

$53

$75

How much do generative ai testing jobs pay per hour?

As of Jul 26, 2026, the average hourly pay for generative ai testing in Austin, TX is $53.25, according to ZipRecruiter salary data. Most workers in this role earn between $43.85 and $61.01 per hour, depending on experience, location, and employer.

What is the difference between Generative Ai Testing vs Data Scientist?

AspectGenerative Ai TestingData Scientist
Required CredentialsKnowledge of AI models, testing tools, programming skillsStatistics, programming, data analysis certifications
Work EnvironmentAI development teams, testing labs, tech companiesResearch labs, tech firms, finance, healthcare
Employer & Industry UsageAI product testing, quality assurance in techData analysis, predictive modeling across industries

Generative Ai Testing focuses on evaluating and validating AI-generated content and models, ensuring quality and accuracy. Data Scientists analyze data, build models, and derive insights. While both roles require programming and AI knowledge, Generative Ai Testing emphasizes testing processes, whereas Data Scientists focus on data analysis and model development.

How much do AI testers get paid?

AI testers, involved in evaluating and validating generative AI models, typically earn salaries ranging from $60,000 to $120,000 annually depending on experience, location, and company size. Entry-level positions may start lower, while experienced testers with specialized skills in machine learning and data analysis can earn higher wages.

Is AI testing a good career?

AI testing, including roles like Generative AI Testing, is a growing field with increasing demand for skills in machine learning, data analysis, and software quality assurance. It offers opportunities in tech companies, research labs, and startups, often requiring knowledge of AI frameworks and testing tools. The career can be stable and rewarding for those with technical expertise and an interest in AI development.

What are the key skills and qualifications needed to thrive as a Generative AI Testing Specialist, and why are they important?

To thrive as a Generative AI Testing Specialist, you need a robust understanding of machine learning principles, model evaluation techniques, and a background in computer science or a related field. Familiarity with tools such as Python, TensorFlow, PyTorch, and model evaluation frameworks, as well as experience with automated testing platforms, is typically required. Analytical thinking, attention to detail, and strong communication skills help you identify model weaknesses and collaborate effectively with development teams. These skills are crucial to ensure the reliability, safety, and ethical deployment of generative AI solutions.

What is the salary of generative AI tester?

The salary of a generative AI tester typically ranges from $70,000 to $120,000 annually, depending on experience, location, and company size. Entry-level positions may start lower, while experienced testers with specialized skills in AI and machine learning can earn higher salaries. Certifications in AI or related fields can also influence compensation.

What are some common challenges faced when testing generative AI models, and how can I prepare to address them in this role?

Testing generative AI models often involves unique challenges such as evaluating the quality and relevance of generated content, detecting bias or inappropriate outputs, and ensuring model consistency across various prompts. You may work closely with data scientists and engineers to create robust evaluation frameworks and develop automated as well as manual testing strategies. Familiarity with prompt engineering, statistical evaluation techniques, and domain-specific knowledge will help you address these challenges effectively. Proactively staying updated on industry best practices and collaborating with cross-functional teams are key to success in this dynamic field.

How do I become an AI tester?

To become an AI tester, you should have a strong understanding of machine learning concepts, programming skills in languages like Python, and experience with data annotation and model evaluation. Familiarity with AI tools, testing frameworks, and quality assurance processes is also important. Gaining relevant certifications or training in AI and software testing can enhance your qualifications.

What is Generative AI Testing?

Generative AI Testing refers to the process of evaluating and validating AI systems, particularly those that generate content such as text, images, or code. This type of testing focuses on assessing the accuracy, reliability, fairness, and safety of generative models to ensure they function as intended and avoid producing harmful or biased outputs. Testers use various methods, including automated and manual techniques, to check for issues like hallucinations, inappropriate content, or security vulnerabilities. The goal is to build trust in generative AI systems and ensure they meet quality and ethical standards before deployment.
What are popular job titles related to Generative Ai Testing jobs in Austin, TX? For Generative Ai Testing jobs in Austin, TX, the most frequently searched job titles are:
What job categories do people searching Generative Ai Testing jobs in Austin, TX look for? The top searched job categories for Generative Ai Testing jobs in Austin, TX are:
What cities near Austin, TX are hiring for Generative Ai Testing jobs? Cities near Austin, TX with the most Generative Ai Testing job openings:
Generative Ai Testing jobs near you
Infographic showing various Generative Ai Testing job openings in Austin, TX as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $110,768 per year, or $53.3 per hour.

Automation Engineer - Playwright - W2 role

NAAS Technologies LLC

Austin, TX • On-site

Contractor

Posted 13 days ago

Job description

Automation Engineer

Austin, TX - Onsite

6+ Months

Responsibilities:

Test Automation & Engineering

  • Design, build, and maintain scalable, reusable automation frameworks for web, mobile, and API testing
  • Implement automated suites that integrate into CI/CD pipelines and improve release confidence
  • Leverage AI- and ML-powered testing tools to enhance coverage, speed, and overall QA intelligence

Manual & Exploratory Testing

  • Conduct hands-on functional, regression, and exploratory testing across apps and platform
  • Identify edge cases, user experience gaps, and defects through deep investigative testing
  • Apply risk-based testing practices to prioritize where time and focus matter most

Quality Leadership & Collaboration

  • Partner with engineering and product teams to define testing strategies throughout the development lifecycle
  • Advocate for quality by raising risks early, validating requirements, and improving testability
  • Take ownership of quality outcomes, proactively identifying gaps and guiding continuous improvement efforts

Innovation & Continuous Improvement

  • Experiment with Generative AI tools to enhance efficiency and expand automation coverage
  • Drive improvements to test frameworks, tooling, and processes across engineering teams
  • Contribute ideas that impact product functionality, reliability, and customer experience, not just QA processes

Qualifications

  • 8+ years of combined automation and manual testing experience
  • Proficiency in at least one programming language: TypeScript, Java, Python, or JavaScript
  • Experience with automation tools such as Playwright, Cypress, Selenium, WebdriverIO, or Appium
  • Strong understanding of manual testing, exploratory techniques, and risk-based testing
  • Experience working in fast-paced startup or agile environments
  • Interest in or experience with AI-powered and Generative AI testing tools
  • Strong problem-solving skills and an inquisitive mindset
  • Ability to collaborate across cross-functional teams and contribute beyond traditional QA responsibilities
  • Experience with CI/CD pipelines and DevOps practices
  • Familiarity with cloud environments such as AWS, GCP, or Azure
  • Experience with data-driven testing or validating analytics pipelines
  • Contributions to open-source testing tools or personal engineering projects
  • Ability to write maintainable test code that supports long-term scalability