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Entry Level Generative Ai Prompt Engineer Jobs in Dallas, TX

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)

Python / GenAI Developer

Dallas, TX · On-site

$50 - $68.75/hr

Fine-tune, evaluate, and deploy Generative AI models for automated financial analysis and ... Data Ingestion: Assist in building data pipelines, prompt engineering, and parsing banking ...

Damco Solutions is seeking a Generative AI Specialist responsible for designing, developing, and ... programming skills in languages such as Python, TensorFlow, or PyTorch • Experience with deep ...

Data Scientist

Irving, TX · On-site

$111K - $131K/yr

Experience with Generative AI, Prompt Engineering, and LLM optimization. * Knowledge of Retrieval-Augmented Generation (RAG) frameworks. * Experience with Azure AI, Azure OpenAI, AWS AI Services, or ...

Showing results 41-60

Entry Level Generative Ai Prompt Engineer information

See Dallas, TX salary details

$29.7K

$68.6K

$116.7K

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

As of Sep 3, 2026, the average yearly pay for entry level generative ai prompt 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 is an entry level generative AI prompt engineer?

Entry Level Generative AI Prompt Engineers are professionals who design, test, and refine prompts to interact with generative AI models, such as those used in chatbots or content creation tools. Their role involves understanding how AI responds to different inputs, troubleshooting issues, and optimizing prompts for accuracy and relevance. They typically collaborate with developers, data scientists, and content teams to improve AI outputs for various applications. This entry-level position is ideal for those with basic programming knowledge, strong communication skills, and an interest in artificial intelligence.

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

To thrive as an Entry Level Generative AI Prompt Engineer, you need a foundational understanding of natural language processing, basic programming skills (often in Python), and familiarity with AI concepts, typically supported by a relevant degree or coursework. Experience with AI platforms like OpenAI, Hugging Face, or Google Cloud AI, as well as prompt design tools, is commonly required. Creativity, analytical thinking, and strong written communication help you craft effective prompts and collaborate with cross-functional teams. These skills are crucial for developing high-quality AI outputs and ensuring solutions align with user needs and project goals.

What are some common challenges faced by entry level generative AI prompt engineers, and how can they overcome them?

Entry-level generative AI prompt engineers often encounter challenges such as crafting effective prompts that yield reliable outputs, staying current with rapidly evolving AI models, and interpreting ambiguous model responses. Overcoming these challenges requires continuous learning, experimentation, and collaboration with more experienced engineers or data scientists. Participating in team discussions, reviewing prompt libraries, and regularly testing prompts with different models can help newcomers build their expertise and confidence in the role.

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

AspectEntry Level Generative Ai Prompt EngineerEntry Level Data Scientist
Required CredentialsBachelor's in CS, AI, or related; basic understanding of AI modelsBachelor's in CS, Statistics, or related; knowledge of data analysis
Work EnvironmentAI labs, tech companies, startupsData analysis teams, research institutions, tech firms
Industry UsageAI development, NLP, chatbot creationData analysis, predictive modeling, research

While both roles require a foundational understanding of technology and data, Entry Level Generative Ai Prompt Engineers focus on designing prompts for AI models, especially in NLP, whereas Entry Level Data Scientists analyze data to derive insights. The roles overlap in technical skills but differ in application and focus areas.

What are the most commonly searched types of Generative Ai Prompt Engineer jobs in Dallas, TX?

The most popular types of Generative Ai Prompt Engineer jobs in Dallas, TX are:

What are popular job titles related to Entry Level Generative Ai Prompt Engineer jobs in Dallas, TX?

For Entry Level Generative Ai Prompt Engineer jobs in Dallas, TX, the most frequently searched job titles are:

What job categories do people searching Entry Level Generative Ai Prompt Engineer jobs in Dallas, TX look for?

The top searched job categories for Entry Level Generative Ai Prompt Engineer jobs in Dallas, TX are:

Infographic showing various Entry Level Generative Ai Prompt Engineer 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 $68,615 per year, or $33 per hour.

AI Intern - Dallas, TX

Black Box Corporation

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.