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

United Software Group Inc

AI Lead (Generative AI)

Irving, TX · On-site

$160K/yr

AI Lead (Generative AI) Location : Irving, TX OR Tampa, FL (Hybrid Onsite -3 Days Onsite Per Week ... Participate in code reviews, testing, and documentation to ensure quality and reliability. * Stay ...

New

SumasEdge Corporation

Generative AI Lead

Irving, TX · On-site

$134K - $165K/yr

Participate in code reviews, testing, and documentation to ensure quality and reliability. * Stay ... Experience with generative AI tools (LangChain, Hugging Face, LlamaIndex) is a plus.

New

Innorev Technologies, Inc

AI Lead( Generative AI)

Irving, TX · On-site

$134K - $165K/yr

... reviews, testing, and documentation to ensure quality and reliability. · Stay updated with ... Experience with generative AI tools (LangChain, Hugging Face, LlamaIndex) is a plus. · ...

New

Droisys

Generative AI LangGraph experience

Plano, TX · On-site

Generative AI Engineer with LangGraph experience Plano, TX- Fully Onsite from Day-1 Core Technical ... Expertise in designing, testing, and optimizing prompts for generative models to achieve desired ...

Citi

Junior Generative AI Application Developer

Irving, TX · Hybrid

$64K - $83K/yr

... testing cycles and post-production deployment. To deliver systems at the enterprise-level that are ... React or Angular, Apigee TypeScript, HTML5 Generative AI & AI Agents: Prompt Engineering, Workflow ...

Citi

Junior Generative AI Application Developer

Irving, TX · Hybrid

$64K - $83K/yr

... testing cycles and post-production deployment To deliver systems at the enterprise-level that are ... React or Angular, Apigee TypeScript, HTML5 Generative AI & AI Agents: Prompt Engineering, Workflow ...

Noblesoft Technologies

Gen AI Lead

Dallas, TX · On-site

$138K - $170K/yr

... Generative * AI, Causal Inference, Time series analysis, Forecasting, Anomaly detection, Hypothesis testing, A/B testing, Git Actions, Tableau, Power BI, ThoughtSpot, Web Scraping * Data ...

Black Box

AI Engineer Intern - USA

Plano, TX · On-site

This role offers hands-on experience building enterprise-grade Generative AI solutions across ... Support testing, debugging, deployment, and monitoring of AI services on Azure. * Document AI ...

Black Box

AI Intern - Dallas, TX

Plano, TX · On-site

This role offers hands-on experience building enterprise-grade Generative AI solutions across ... Support testing, debugging, deployment, and monitoring of AI services on Azure. * Document AI ...

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

Generative Ai Testing information

See McKinney, TX salary details

$29

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How much do generative ai testing jobs pay per hour?

As of Aug 31, 2026, the average hourly pay for generative ai testing in McKinney, TX is $49.86, according to ZipRecruiter salary data. Most workers in this role earn between $41.06 and $57.12 per hour, depending on experience, location, and employer.

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 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.

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 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 do I become a Generative AI Testing?

To become a Generative AI Tester, develop skills in machine learning, natural language processing, and programming languages like Python. Gain experience with AI frameworks such as TensorFlow or PyTorch and understand data quality and model evaluation techniques. Relevant certifications and hands-on projects can enhance your qualifications for roles in AI testing environments.

Is Generative AI Testing a good career?

Generative AI Testing is a growing field within AI development, focusing on evaluating the quality and safety of AI-generated content. It requires skills in machine learning, programming, and understanding AI models, often involving tools like Python and TensorFlow. The role offers opportunities in tech companies and research labs, with demand expected to increase as AI applications expand.

What are popular job titles related to Generative Ai Testing jobs in McKinney, TX?

For Generative Ai Testing jobs in McKinney, TX, the most frequently searched job titles are:

What job categories do people searching Generative Ai Testing jobs in McKinney, TX look for?

The top searched job categories for Generative Ai Testing jobs in McKinney, TX are:

What cities near McKinney, TX are hiring for Generative Ai Testing jobs?

Cities near McKinney, TX with the most Generative Ai Testing job openings:

Generative Ai Testing jobs near you
Infographic showing various Generative Ai Testing job openings in McKinney, TX as of August 2026, with employment types broken down into 75% Full Time, and 25% Contract. Highlights an 100% In-person job distribution, with an average salary of $103,708 per year, or $49.9 per hour.

AI Lead (Generative AI)

Irving, TX • On-site

United Software Group Inc
IT Services • 201 - 500 employees
Learn more about United Software Group Incexternal

$160K/yr

Other

Posted yesterday

New

Job description

Job Title: AI Lead (Generative AI)

Location : Irving, TX OR Tampa, FL (Hybrid Onsite -3 Days Onsite Per Week)

Duration : Fulltime

Teams Meeting Interview

Job Description:


Key Responsibilities:


  • Contribute to prompt engineering and development of AI-powered workflows
  • Assist with the deployment, monitoring, and maintenance of AI models in production environments.
  • Collaborate with data scientists and engineers to ensure seamless integration of AI capabilities.
  • Perform data preprocessing, feature engineering, and API development for AI applications.
  • Participate in code reviews, testing, and documentation to ensure quality and reliability.
  • Stay updated with advancements in GenAI and share relevant learnings with the team.


Required Technical Skills:


  • Familiarity with LLMs, prompt engineering, and workflow orchestration.
  • Exposure to RAG systems and basic knowledge of hybrid search techniques.
  • Exposure to Multi-Agent systems.
  • Understanding of model deployment and containerization (Docker).
  • Proficiency in Python for AI development, data preprocessing, and scripting.
  • Experience with generative AI tools (LangChain, Hugging Face, LlamaIndex) is a plus.
  • Understanding of version control systems (Git).
  • Awareness of AI compliance, data privacy, and responsible AI principles.
  • Hands-on experience with at least one major machine learning framework (PyTorch, TensorFlow, Keras). (Advantageous)


Required Soft Skills:


  • Strong teamwork and communication abilities.
  • Willingness to learn new AI/ML technologies and frameworks.
  • Analytical mindset and attention to detail.
  • Openness to feedback and continuous improvement.


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