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Generative Ai Developer Jobs in Dallas, TX (NOW HIRING)

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)

Senior AI Developer

Southlake, TX · On-site

$81.90 - $91/hr

Lead the integration and application of Generative AI coding assistants throughout the System ... Collaborate with fellow developers, architects, and adjacent teams, fostering a culture of ...

Position Overview Citi is looking for a Principal Generative AI Engineer to lead the design, development, and deployment of intelligent operations and automation platforms within the AI Automation ...

New

Experience with Generative AI Large Language Models (LLMs), including solution development and fine-tuning for domain-specific tasks. * Proficiency in at least one programming language such as Python ...

Experience with Generative AI Large Language Models (LLMs), including solution development and fine-tuning for domain-specific tasks. * Proficiency in at least one programming language such as Python ...

... in Generative AI-related fields Qualifications : Required : • Strong hands-on Python knowledge ... Engineering, RAG Architecture, Agentic AI. • Basic knowledge of Hybrid prompting technique • ...

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Generative Ai Developer information

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$18

$44

$100

How much do generative ai developer jobs pay per hour?

As of Sep 1, 2026, the average hourly pay for generative ai developer in Dallas, TX is $44.99, according to ZipRecruiter salary data. Most workers in this role earn between $23.41 and $54.47 per hour, depending on experience, location, and employer.

What is a generative AI developer?

A Generative AI Developer is a technology professional who specializes in designing, building, and deploying artificial intelligence systems that can create new content, such as text, images, audio, or code. They work with advanced machine learning models, like generative adversarial networks (GANs) or large language models, to enable computers to produce original outputs. These developers often collaborate with data scientists, researchers, and product teams to integrate AI-generated content into software applications and business solutions.

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

To thrive as a Generative AI Developer, you need strong programming skills (especially in Python), a deep understanding of machine learning concepts, and an advanced degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and experience with cloud platforms or model deployment tools are typically required. Creative problem-solving, adaptability, and effective collaboration are standout soft skills in this evolving field. These abilities are crucial to design, implement, and refine generative models that solve real-world problems and drive innovation.

What are some common challenges faced by generative AI developers when deploying models in production environments?

Generative AI Developers often encounter challenges such as ensuring model reliability, managing computational resource requirements, and addressing ethical considerations like data bias or content safety. Deploying generative models at scale requires robust monitoring to detect unexpected outputs or model drift, and collaboration with data engineers and product teams to optimize performance. Staying up-to-date with evolving frameworks and best practices is essential, as production environments demand both technical rigor and adaptability to new AI advancements.

What is the difference between Generative Ai Developer vs Machine Learning Engineer?

AspectGenerative Ai DeveloperMachine Learning Engineer
CredentialsBachelor's or higher in CS, AI, or related fields; experience with deep learning frameworksBachelor's or higher in CS, Data Science, or related fields; strong programming skills
Work EnvironmentDevelops AI models for content creation, chatbots, and creative applicationsBuilds and deploys ML models for various data-driven solutions across industries
Industry UsageTech, entertainment, marketing, and creative sectorsFinance, healthcare, tech, and e-commerce sectors

While both roles involve AI and machine learning, Generative Ai Developers focus on creating models that generate content, such as images or text, whereas Machine Learning Engineers develop broader ML solutions for diverse applications. The roles often overlap but differ mainly in their specific focus areas and use cases.

How to become a generative AI developer?

To become a generative AI developer, you should have a strong foundation in programming languages like Python, experience with machine learning frameworks such as TensorFlow or PyTorch, and knowledge of neural network architectures like transformers. Gaining expertise in natural language processing and deep learning, along with practical experience through projects or internships, is essential. Certifications in AI or data science can also enhance your qualifications.

What are popular job titles related to Generative Ai Developer jobs in Dallas, TX?

For Generative Ai Developer jobs in Dallas, TX, the most frequently searched job titles are:

What job categories do people searching Generative Ai Developer jobs in Dallas, TX look for?

The top searched job categories for Generative Ai Developer jobs in Dallas, TX are:

What cities near Dallas, TX are hiring for Generative Ai Developer jobs?

Cities near Dallas, TX with the most Generative Ai Developer job openings:

Infographic showing various Generative Ai Developer job openings in Dallas, TX as of August 2026, with employment types broken down into 78% Full Time, 18% Part Time, and 4% Contract. Highlights an 71% Physical, 4% Hybrid, and 25% Remote job distribution, with an average salary of $93,582 per year, or $45 per hour.

AI Intern - Dallas, TX

Black Box

Plano, TX • On-site

Part-time

Re-posted 6 days ago


Job description


AI Engineer Intern - AI Center of Excellence (CoE)
Location: Plano, Texas, USA
Internship Duration: 6-12 months (12 months preferred)
Company: Black Box
Eligibility: Master's students with at least 6 months remaining before graduation and prior professional experience in applied AI
Company Overview
Black Box Network Services is a leading global communications system integrator specializing in designing, sourcing, implementing, and managing complex technology solutions. As part of our strategic transformation, Black Box is expanding its AI Center of Excellence (CoE) to deliver enterprise-grade AI solutions across multiple business domains.
The AI CoE focuses on building scalable, secure, and production-ready AI systems, establishing best practices for enterprise AI adoption, and integrating AI capabilities into core business platforms.
Role Summary
As an AI Engineer Intern in the AI Center of Excellence (CoE), you will contribute to the design, development, and integration of applied AI solutions using pre-trained Large Language Models (LLMs), traditional machine learning techniques, and deterministic approaches.
This role offers hands-on experience building enterprise-grade Generative AI solutions across backend services, data pipelines, orchestration, and user-facing applications. Working closely with experienced AI engineers, you will contribute to real-world AI use cases integrated with platforms such as ServiceNow, SAP, Salesforce, and Azure services.
This internship is designed to strengthen applied AI engineering skills and prepare candidates for conversion into a full-time AI Engineer role.
Eligibility Requirements
  • Currently pursuing a Master's degree in Engineering or a related field (Computer Science, Artificial Intelligence, Data Science, or similar).
  • Must have at least 6 months remaining to complete the Master's program at the time of joining.
  • Must have a minimum of 2 years of relevant professional experience between Bachelor's and Master's programs.
  • Prior experience must include applied AI / Machine Learning, with hands-on exposure to Generative AI use cases.
  • Available for a full-time, on-site internship for a minimum of 6-12 months (depending on academic program constraints).

Key Responsibilities AI & Generative AI Development
  • Build and integrate AI solutions using pre-trained LLMs for conversational AI, summarization, and enterprise knowledge retrieval.
  • Implement RAG-based architectures connecting LLMs with structured and unstructured enterprise data.
  • Develop and test AI agents, traditional ML models, and deterministic logic for real-world use cases.
  • Contribute to AI orchestration using LangChain and workflow automation using n8n.

Full-Stack & Enterprise Integration
  • Build AI-enabled user interfaces and integrate them with backend services.
  • Develop and maintain backend APIs and services.
  • Integrate AI solutions with enterprise platforms such as ServiceNow, SAP, Salesforce, and Azure services.

Data, Testing & Deployment
  • Build and maintain data pipelines, including preprocessing and quality checks.
  • Support testing, debugging, deployment, and monitoring of AI services on Azure.
  • Document AI workflows, integrations, and solution lifecycle updates.

Learning & Collaboration
  • Collaborate with AI, data, and platform teams to deliver production-ready AI solutions.
  • Continuously learn and apply best practices in Generative AI, RAG patterns, and enterprise AI systems.

Required Technical Skills
  • Programming: Strong working knowledge of Python.
  • Applied AI / GenAI: Hands-on experience building or integrating ML or Generative AI solutions.
  • 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).
  • Frontend Development: Working experience building React-based user interfaces and integrating them with backend APIs.
  • Data Handling: Experience working with structured and unstructured data, including basic preprocessing or ETL.
  • APIs & Cloud: Experience consuming REST APIs and familiarity with cloud platforms (Azure preferred).

Required Prior Professional Experience
  • 2+ years of relevant professional experience between Bachelor's and Master's programs.
  • Experience in applied AI, machine learning, or software engineering with AI components.
  • Ability to translate AI concepts into working prototypes or production-ready solutions.

Required Soft Skills
  • Strong learning mindset, ownership, and clear communication with a structured problem-solving approach.

Preferred Skills / Experience
  • Familiarity with NLP concepts and foundational Generative AI models.
  • Awareness of responsible AI and basic AI governance concepts.
  • Exposure to Microsoft Power Platform or low-code automation tools.

About Black Box
Black Box is a leading technology solutions provider focused on accelerating customer success through innovation, ownership, transparency, and collaboration. With over 2,500 team members across 24 countries, Black Box delivers high-value solutions globally and is a wholly-owned subsidiary of AGC Networks. Black Box is an equal opportunity employer.