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Entry Level Generative Ai Engineer Jobs in Dallas, TX

Droisys

Generative AI Engineer

Dallas, TX · On-site

Generative AI EngineerIntroduction: The Generative AI Engineer will be responsible for developing and implementing Generative AI solutions using various technologies such as LLMs, RAG, Prompt ...

Stackruit Ltd.

Generative AI Engineer

Dallas, TX · On-site

$100 - $130/hr

Become an Azure AI Engineer and: Collaborate with clients to design and build impactful AI solutions on Microsoft Azure. Work on various project phases, from ideation to deployment, across generative ...

New

Black Box

AI Engineer Intern - USA

Plano, TX · On-site

AI Engineer Intern - AI Center of Excellence (CoE) Location: Plano, Texas, USA Internship Duration ... This role offers hands-on experience building enterprise-grade Generative AI solutions across ...

Cognizant

Generative AI Lead Engineer

Dallas, TX · On-site

$120 - $140/hr

About the role As a Generative AI Engineer , you will make an impact by designing and building advanced AI-powered applications and scalable solutions using modern technologies such as .NET, React ...

New

Black Box

AI Intern - Dallas, TX

Plano, TX · On-site

Generative AI: Practical experience with LLMs, prompt engineering, and/or RAG-based architectures. * Backend Development: Experience building APIs using FastAPI, Flask, or Node.js (TypeScript)

ITBMS Inc.

AI Engineer

Plano, TX · On-site

AI Engineer Location: Plano, TX, Wilmington, DE, Columbus, OH Duration: Contract Key ... Experience with Generative AI and Large Language Models (LLMs). * Knowledge of RAG, embeddings, and ...

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Entry Level Generative Ai Engineer information

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$29.7K

$68.6K

$116.7K

How much do entry level generative ai engineer jobs pay per year?

As of Aug 7, 2026, the average yearly pay for entry level generative ai engineer in Dallas, TX is $68,615.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,900.00 and $77,700.00 per year, depending on experience, location, and employer.

What are common challenges faced by entry level generative AI engineers, and how can they be addressed?

Entry level Generative AI Engineers often encounter challenges such as mastering complex machine learning frameworks, understanding the nuances of training large models, and keeping up with rapidly evolving research. Collaborating closely with more experienced team members through code reviews and pair programming can accelerate learning. It's also helpful to engage in continuous education through online courses and participate in team discussions to stay updated on the latest advancements and best practices in the field.

What is the difference between Entry Level Generative Ai Engineer vs Data Scientist?

AspectEntry Level Generative Ai EngineerData Scientist
Required CredentialsBachelor's in CS, AI, or related field; basic knowledge of machine learning and programmingBachelor's or higher in CS, Statistics, or related; knowledge of data analysis and modeling
Work EnvironmentTech companies, AI startups, research labs focusing on AI model developmentVarious industries including finance, healthcare, marketing; analyzing data to inform decisions
Employer & Industry UsagePrimarily in AI and tech sectors developing generative modelsAcross multiple sectors using data to solve business problems

While both roles require a background in data and programming, Entry Level Generative Ai Engineers focus on developing AI models like generative adversarial networks, whereas Data Scientists analyze data to generate insights. The former is more specialized in AI model creation, while the latter covers broader data analysis tasks.

What is an entry level generative AI engineer?

Entry level generative AI engineers are professionals who work with artificial intelligence technologies focused on creating new content such as images, text, audio, or code. They typically assist in developing, training, and fine-tuning machine learning models like GPT or GANs under the supervision of senior engineers. These roles usually require a strong foundation in programming, mathematics, and machine learning concepts, but may not demand extensive industry experience. Tasks often include data preprocessing, model evaluation, and contributing to research or product development involving generative AI.

What are the key skills and qualifications needed to thrive as an entry level generative AI engineer?

To thrive as an Entry Level Generative AI Engineer, you need a solid background in computer science, mathematics, and machine learning fundamentals, typically supported by a relevant degree or coursework. Familiarity with Python, deep learning frameworks like TensorFlow or PyTorch, and version control systems such as Git is important, along with any foundational certifications in AI or data science. Strong problem-solving ability, curiosity, and effective teamwork skills will help you stand out in this collaborative and innovative field. These skills and qualities are crucial for developing, testing, and improving generative AI models in a rapidly evolving technical landscape.
What are the most commonly searched types of Generative Ai Engineer jobs in Dallas, TX? The most popular types of Generative Ai Engineer jobs in Dallas, TX are:
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What job categories do people searching Entry Level Generative Ai Engineer jobs in Dallas, TX look for? The top searched job categories for Entry Level Generative Ai Engineer jobs in Dallas, TX are:
What cities near Dallas, TX are hiring for Entry Level Generative Ai Engineer jobs? Cities near Dallas, TX with the most Entry Level Generative Ai Engineer job openings:
Entry Level Generative Ai Engineer jobs near you
Infographic showing various Entry Level Generative Ai Engineer job openings in Dallas, TX as of August 2026, with employment types broken down into 73% Full Time, 11% Part Time, and 16% Contract. Highlights an 84% In-person, 5% Hybrid, and 11% Remote job distribution, with an average salary of $68,615 per year, or $33 per hour.

Generative AI Engineer

Droisys

Dallas, TX • On-site

Other

Posted 17 days ago

Job description

Generative AI EngineerIntroduction:

The Generative AI Engineer will be responsible for developing and implementing Generative AI solutions using various technologies such as LLMs, RAG, Prompt Engineering, AI Agents, LangChain/LangGraph, Semantic Kernel, and vector databases. The role will involve working on backend development, data engineering, API integration, database design, scalability, security, and performance optimization.

Responsibilities:
  • Build Generative AI solutions using technologies like LLMs, RAG, Prompt Engineering, and LangChain/LangGraph.
  • Develop AI Agents and Semantic Kernels for AI-driven enterprise automation solutions.
  • Work on database design, scalability, security, and performance optimization for AI applications.
  • Create REST APIs and Microservices for backend development using Python, Node.js, and Java.
  • Collaborate with cross-functional teams to integrate AI solutions into existing systems.
  • Utilize MongoDB and Azure Data Services for data storage and management.
Requirements:Required Skills:
  • Strong experience in building Generative AI solutions.
  • Proficiency in technologies like LangChain, Generative Artificial Intelligence (AI), and Prompt Engineering.
  • Knowledge of MongoDB for data storage.
  • Experience in performance tuning and database design.
  • Understanding of semantics in AI applications.
Preferred Skills:
  • Experience with React, Angular, TypeScript, JavaScript, HTML5, and CSS3.
  • Familiarity with modern UI frameworks.
  • Expertise in Python, ETL, and Azure AI Search.
  • Backend development skills using Python, Node.js, and Java.

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