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Generative Ai Analyst Jobs in Texas (NOW HIRING)

PB consulting

Generative AI Engineer

Irving, TX · On-site

We are seeking a skilled Generative AI Engineer to design, develop, and deploy advanced AI ... Strong analytical, problem-solving, and communication skills. Preferred Skills * Experience with ...

PB consulting

Generative AI Engineer

Grapevine, TX

We are seeking a skilled Generative AI Engineer to design, develop, and deploy advanced AI ... Strong analytical, problem-solving, and communication skills. Preferred Skills * Experience with ...

Prosum Inc.

Generative AI Engineer

Fort Worth, TX · On-site

$120K - $165K/yr

Generative AI Engineer Location: Remote (U.S.) Salary Range: $120k to $165k About the Role We are ... Lead incident response and root cause analysis, implementing long-term fixes * Develop evaluation ...

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 ... Lead production incident response and root cause analysis, driving systemic improvements that ...

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Generative Ai Analyst information

See Texas salary details

$45.7K

$82.5K

$115.1K

How much do generative ai analyst jobs pay per year?

As of Aug 12, 2026, the average yearly pay for generative ai analyst in Texas is $82,515.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,600.00 and $92,700.00 per year, depending on experience, location, and employer.

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

AspectGenerative Ai AnalystData Scientist
Required CredentialsBachelor's in CS, AI, or related fields; certifications in AI/MLBachelor's/Master's in CS, Statistics, or related fields; advanced certifications
Work EnvironmentTech companies, AI startups, research labsTech firms, finance, healthcare, consulting
Employer & Industry UsageFocus on developing and refining generative AI modelsAnalyze data, build predictive models, derive insights
Common Search & Comparison IntentUnderstanding roles in AI developmentData analysis and modeling skills

While both roles require strong technical skills and knowledge of AI and data analysis, a Generative Ai Analyst specializes in creating and optimizing generative AI models, whereas a Data Scientist focuses on analyzing data to inform business decisions. The roles often overlap but differ in their primary focus and application within organizations.

What are the key skills and qualifications needed to thrive as a generative AI analyst?

To thrive as a Generative AI Analyst, you need a solid background in data science, machine learning, and statistics, often supported by a degree in computer science or a related field. Familiarity with tools and frameworks such as Python, TensorFlow, PyTorch, and experience with large language models or generative adversarial networks (GANs) is typically required. Strong analytical thinking, creativity, and effective communication skills help you interpret complex data and present insights to stakeholders. These skills and qualities are crucial for developing innovative AI solutions, solving business challenges, and driving impactful results.

How does a generative AI analyst typically collaborate with data scientists and engineering teams?

A Generative AI Analyst frequently works alongside data scientists and engineering teams to interpret model outputs, assess data quality, and help translate business objectives into technical requirements. Collaboration usually involves regular meetings to review model performance, troubleshoot issues, and refine algorithms based on real-world feedback. Effective communication and a shared understanding of both AI concepts and business goals are essential, as the analyst often serves as a bridge between technical teams and stakeholders. This collaborative environment fosters continuous learning and innovation, making teamwork a core aspect of the role.

How much do generative AI analysts make?

Generative AI analysts typically earn between $70,000 and $130,000 annually, depending on experience, location, and industry. Entry-level roles may start lower, while experienced professionals with specialized skills in machine learning and natural language processing can earn higher salaries.

What is a generative AI analyst?

A Generative AI Analyst is a professional who specializes in analyzing, designing, and optimizing systems that use generative artificial intelligence models, such as large language models or image generators. Their work involves understanding how these AI models are developed, deployed, and utilized across various applications. They assess data quality, monitor model outputs, evaluate performance, and help improve the effectiveness and ethical use of generative AI technologies. Generative AI Analysts may also provide insights to organizations on best practices, risk management, and innovation opportunities related to AI. Their expertise bridges the gap between data science, AI development, and business strategy.
What are popular job titles related to Generative Ai Analyst jobs in Texas? For Generative Ai Analyst jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Generative Ai Analyst jobs in Texas look for? The top searched job categories for Generative Ai Analyst jobs in Texas are:
What cities in Texas are hiring for Generative Ai Analyst jobs? Cities in Texas with the most Generative Ai Analyst job openings:
Generative Ai Analyst jobs near you
Infographic showing various Generative Ai Analyst job openings in Texas as of August 2026, with employment types broken down into 100% Full Time. Highlights an 60% In-person, and 40% Hybrid job distribution, with an average salary of $82,515 per year, or $39.7 per hour.

Generative AI Engineer

PB consulting

Irving, TX • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

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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