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Generative Ai Testing Jobs in Texas (NOW HIRING)

PB consulting

Generative AI Engineer

Colleyville, TX

Participate in model testing, deployment, monitoring, and continuous improvement. * Contribute to ... Experience with Generative AI techniques including text generation, text-to-image generation, and ...

PB consulting

Generative AI Engineer

Addison, TX

Participate in model testing, deployment, monitoring, and continuous improvement. * Contribute to ... Experience with Generative AI techniques including text generation, text-to-image generation, and ...

PB consulting

Generative AI Engineer

Hurst, TX

Participate in model testing, deployment, monitoring, and continuous improvement. * Contribute to ... Experience with Generative AI techniques including text generation, text-to-image generation, and ...

PB consulting

Generative AI Engineer

Duncanville, TX

Participate in model testing, deployment, monitoring, and continuous improvement. * Contribute to ... Experience with Generative AI techniques including text generation, text-to-image generation, and ...

PB consulting

Generative AI Engineer

Carrollton, TX

Participate in model testing, deployment, monitoring, and continuous improvement. * Contribute to ... Experience with Generative AI techniques including text generation, text-to-image generation, and ...

Lares IT Solutions Inc

Generative AI Engineer

Plano, TX · On-site

Generative AI Developer Plano, TX We are seeking a seasoned Generative AI Developer with expertise ... Testing & Tools: Cucumber (BDD), SonarQube, Postman, JIRA, Maven, Gradle, Apache Spark * Operating ...

Socket.dev

Generative AI Engineer

Lewisville, TX · On-site

$140 - $190/hr

Position Description We are seeking a Generative AI Engineer to own the hands-on technical delivery ... Build and maintain automated evaluation pipelines for LLM outputs - prompt regression testing ...

Introlligent Inc.

QA

Austin, TX · On-site

$41 - $55.75/hr

Develop AI testing and evaluation pipelines using Python. * Collaborate with AI/ML teams to improve AI application quality. Required Skills * Strong experience in AI Engineering , Generative AI , and ...

Cognizant

Generative AI Lead Engineer

Dallas, TX · On-site

$120 - $140/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

About the role As a Generative AI Engineer , you will make an impact by designing and building ... testing, deployment, and code reviews) * Develop scalable architectures leveraging Retrieval ...

Citi

Junior Generative AI Application Developer

Irving, TX · Hybrid

$64K - $83K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... 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 ...

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 ...

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Generative Ai Testing information

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. Certifications in AI or data science can enhance your qualifications and improve job prospects.

Is Generative AI Testing a good career?

Generative AI Testing is a growing field within AI development that involves evaluating the quality and safety of AI-generated content. It requires skills in machine learning, programming, and understanding AI models, making it a promising career path with increasing demand as AI technologies expand. Professionals in this area can find opportunities in tech companies, research labs, and startups focused on AI innovation.

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 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 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 Texas?

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

What job categories do people searching Generative Ai Testing jobs in Texas look for?

The top searched job categories for Generative Ai Testing jobs in Texas are:

What cities in Texas are hiring for Generative Ai Testing jobs?

Cities in Texas with the most Generative Ai Testing job openings:

Generative Ai Testing jobs near you
Infographic showing various Generative Ai Testing job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 86% Full Time, 9% Part Time, 3% Contract, and 1% Nights. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.

Generative AI Engineer

PB consulting

Colleyville, TX

Full-time

Posted 12 days ago

Job description

We are seeking a skilled Generative AI Engineer to design, develop, and deploy advanced AI solutions that solve complex business challenges. The ideal candidate will have strong expertise in Python, Large Language Models (LLMs), machine learning, deep learning, and Natural Language Processing (NLP), with hands-on experience building and optimizing generative AI applications using open-source models and modern AI frameworks.

Roles and Responsibilities

  • Design, develop, and implement advanced AI and Generative AI solutions to address complex business requirements.

  • Collaborate with engineers, researchers, product managers, and business stakeholders to translate business needs into scalable AI solutions.

  • Collect, clean, prepare, and engineer data for training, fine-tuning, and evaluating AI models while ensuring data quality and integrity.

  • Develop and optimize machine learning, deep learning, and NLP models for enterprise applications.

  • Build and deploy Generative AI solutions using Large Language Models (LLMs), text generation, and text-to-image generation techniques.

  • Evaluate, compare, and optimize AI model architectures, hyperparameters, and performance metrics.

  • Apply responsible AI practices by identifying model bias, improving fairness, and ensuring ethical AI development.

  • Develop scalable AI solutions that integrate with enterprise applications and cloud platforms.

  • Participate in model testing, deployment, monitoring, and continuous improvement.

  • Contribute to AI best practices, technical documentation, and knowledge sharing across teams.

Required Skills

  • Strong proficiency in Python with major machine learning and deep learning libraries.

  • Hands-on experience with open-source Large Language Models (LLMs) such as Llama, Dolly, or similar models.

  • Strong knowledge of Machine Learning, Deep Learning, Natural Language Processing (NLP), neural networks, transformers, supervised and unsupervised learning.

  • Experience with Generative AI techniques including text generation, text-to-image generation, and Generative Adversarial Networks (GANs).

  • Experience with data preprocessing, feature engineering, SQL, and data manipulation.

  • Familiarity with AI model evaluation, optimization, and hyperparameter tuning.

  • Strong analytical, problem-solving, and communication skills.

Preferred Skills

  • Experience with cloud platforms including AWS, Microsoft Azure, or Google Cloud Platform (GCP).

  • Experience developing AI applications in both on-premises and cloud environments.

  • Knowledge of CI/CD pipelines and AI application deployment practices.

  • Familiarity with MLOps, model lifecycle management, and scalable AI deployment architectures.

Qualifications

  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.

  • Experience designing, developing, and deploying enterprise AI or Generative AI solutions.

  • Ability to work effectively in cross-functional teams and deliver high-quality AI solutions in an agile environment.

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