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

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 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 ...

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 ...

Precision Technologies Corp

AI Engineer

Dallas, TX · On-site

Stay current with cutting-edge AI research (Generative AI, RAG, agentic frameworks). * Perform testing, validation, and performance tuning for compliance and reliability. * Research and publish ...

Infosys Limited Digital

Gen AI Engineer

Dallas, TX · On-site

... Generative AI|Conversational AI Platform Technical Skills 2 Technology|Generative AI|Prompt ... testing and optimize algorithms for performance, reliability, and scalability, while providing ...

Infosys Limited Digital

Gen AI Engineer

Dallas, TX · On-site

... Generative AI|Conversational AI Platform Technical Skills 2 Technology|Generative AI|Prompt ... testing and optimize algorithms for performance, reliability, and scalability, while providing ...

Infosys Limited Digital

Gen AI Engineer

Dallas, TX · On-site

... Generative AI|Conversational AI Platform Technical Skills 2 Technology|Generative AI|Prompt ... testing and optimize algorithms for performance, reliability, and scalability, while providing ...

Infosys Limited Digital

Gen AI Engineer

Dallas, TX · On-site

... Generative AI|Conversational AI Platform Technical Skills 2 Technology|Generative AI|Prompt ... testing and optimize algorithms for performance, reliability, and scalability, while providing ...

Infosys Limited Digital

Gen AI Engineer

Dallas, TX · On-site

... Generative AI|Conversational AI Platform Technical Skills 2 Technology|Generative AI|Prompt ... testing and optimize algorithms for performance, reliability, and scalability, while providing ...

Morgan Stanley

VP, AI Compliance Officer

Dallas, TX · On-site

$108K - $185K/yr

What you'll do in the role: > Advise Wealth Management Generative AI and Platforms teams on AI ... Testing teams. > Collaborate with Policy and Training teams to draft, implement, and maintain ...

Morgan Stanley

VP, AI Compliance Officer

Dallas, TX · On-site

$108K - $185K/yr

What you'll do in the role: > Advise Wealth Management Generative AI and Platforms teams on AI ... Testing teams. > Collaborate with Policy and Training teams to draft, implement, and maintain ...

NTT DATA, Inc.

AI Engineering Associate Director

Plano, TX · On-site

$151.40 - $202.50/hr

Design, develop, and implement AI and generative AI solutions across primarily healthcare, life ... Participate in testing, debugging, performance tuning, deployment, documentation, and operational ...

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

Generative Ai Testing information

See Prosper, TX salary details

$29

$49

$70

How much do generative ai testing jobs pay per hour?

As of Aug 11, 2026, the average hourly pay for generative ai testing in Prosper, TX is $49.20, according to ZipRecruiter salary data. Most workers in this role earn between $40.53 and $56.35 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 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 job categories do people searching Generative Ai Testing jobs in Prosper, TX look for? The top searched job categories for Generative Ai Testing jobs in Prosper, TX are:
What cities near Prosper, TX are hiring for Generative Ai Testing jobs? Cities near Prosper, TX with the most Generative Ai Testing job openings:
Generative Ai Testing jobs near you
Infographic showing various Generative Ai Testing job openings in Prosper, TX as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 14% Part Time, 5% Contract, and 1% Nights. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $102,339 per year, or $49.2 per hour.

Gen AI Lead

Noblesoft Technologies

Dallas, TX • On-site

$138K - $170K/yr

Contractor

Re-posted 10 days ago

Job description

Job Title: Gen AI Lead
Mandatory Skills: Gen AI/Agentic AI /ML
 
JD: 
 
JOB DESCRIPTION:
Keywords: AI/ML Development, Generative AI, LLMs, Python, Web Frameworks, MLOps, Data Engineering
 
Role Overview:
Sr AI/ML Lead with around 15+ years of hands-on experience in developing and implementing Machine Learning and Generative AI solutions. The role involves designing, developing, and deploying end-to-end AI/ML applications using Python, popular ML frameworks, and modern web technologies.
 
 
TECHNICAL SKILLS: Must Have Skills
  • Machine learning development lifecycle - (Data preparation, Data visualization, Statistical Analysis, feature engineering, Predictive modeling, Model deployment, Model monitoring), CI/CD, MLOps, Generative
  • AI, Causal Inference, Time series analysis, Forecasting, Anomaly detection, Hypothesis testing, A/B testing, Git Actions, Tableau, Power BI, ThoughtSpot, Web Scraping
  • Data & Engineering – SQL, MySQL, Postgres, Spark, S3, Trino, Data Factory, ETL, Data pipelines, Databricks and distributed computing.
  • Programming Languages: SQL, Pyspark, Scala, R, Python, SAS
  • Gen AI & Agents – Prompt Engineering, RAG, Vector DB, Agentic Frameworks, MCP, Large Language Models (LLMs),LangChain, LangGraph, Explainable AI, Conversational AI, Chat bots and Tuning, LLM Evaluations and Cost monitoring, HuggingFace
  • Tools/Framework: Git, TensorFlow, PyTorch, PySpark, AWS, MLflow, Docker, Kubernetes, Databricks, SparkSQL, OpenCV, Azure, YOLO, Scikit-Learn, FastAPI, Flask, Django, Keras, Pandas, NumPy, Polars, SciPy, Matplotlib, Seaborn,Plotly, Streamlit
  • Cloud & MLOps: AWS Sagemaker, Azure ML, or GCP AI Platform; Git, Docker, CI/CD.
 
 
 
Role Activities:
  • Design, develop, and deploy AI/ML and Generative AI models for enterprise and telecom use cases.
  • Build and optimize data pipelines for training, validation, and inference processes.
  • Develop web-based AI applications using frameworks like Flask, FastAPI, or Django.
  • Implement LLM-based solutions such as chatbots, summarization, and RAG-based systems.
  • Collaborate with data scientists, solution architects, and business teams to understand functional requirements and translate them into technical implementations.
  • Participate in proof-of-concept (PoC) development for AI/ML and automation use cases.
  • Conduct model evaluation, fine-tuning, and performance optimization.
  • Work with APIs, data sources, and cloud-based ML services (AWS, Azure, GCP).
  • Follow best practices in MLOps, model versioning, and CI/CD integration.
  • Prepare technical documentation, training materials, and demo presentations.

Domain Skills Requirements:
  • At least 10+ years of experience in AI/ML development and Python-based solutions for Telco/Retail Domains
  • Desired Domain Experienced
    • Telecom BSS & OSS domain and understanding of fixed, mobile, IoT & convergence domains and related markets 
    • Business Systems (BSS)- Understanding of E2E BSS Solutions across Sales, Marketing, Finance, Product Management, Care areas for CSPs. 
    • Knowledge on data integration for telecom industry B/OSS COTS  & Data Models ( Amdocs, NetCracker, CSG etc.)
 
Preferred Qualifications:
  • Certification in AI/ML, Deep Learning, or Generative AI is a plus.