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Freelance Generative Ai Prompt Engineer Jobs (NOW HIRING)

Generative AI Engineer Location Dallas, TX or Charlotte, NC or Raleigh, NC Role Overview We are ... Develop and optimize advanced prompt engineering strategies to improve LLM performance, accuracy ...

New

AI Architect

Manhattan, NY · On-site

$69.50 - $91.50/hr

Agent AI, Prompt Engineering, Generative AI : AI Product & Copilot Agent Specialist We are seeking a highly technical and innovative professional with deep expertise in Generative AI, Microsoft 365 ...

New

We are seeking a Prompt Engineer design, test, and refine interaction patterns for generative AI systems used across our client engagements. This role is central to shaping how users experience AI ...

Prompt Engineer

Mclean, VA · On-site

$115K - $140K/yr

Overview We are seeking a Prompt Engineer design, test, and refine interaction patterns for generative AI systems used across our client engagements. This role is central to shaping how users ...

Overview We are seeking a Prompt Engineer design, test, and refine interaction patterns for generative AI systems used across our client engagements. This role is central to shaping how users ...

Key Responsibilities Generative AI & Prompt Engineering * Design, develop, and optimize applications leveraging internal LLM platforms * Create, test, and maintain high-quality prompts to drive ...

This role focuses on Generative AI, Large Language Models (LLMs), Prompt Engineering, Agentic AI systems, Machine Learning, Data Science, and AWS-based cloud engineering. The ideal candidate will ...

Generative AI Architect

Charlotte, NC · On-site

$61.50 - $81/hr

Generative AI Architect Location: Charlotte, NC (Onsite from Day 1) Job Type: Contract Skill ... and prompt engineering frameworks 3. Participate in cross-functional GenAI initiatives and PoC ...

Generative AI Lead

Pleasanton, CA · On-site

$185K/yr

Generative AI Lead We are hiring a Generative AI Lead to spearhead AI innovation at our Pleasanton ... Oversee prompt engineering, fine-tuning, RLHF, and model evaluation practices * Build responsible ...

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Freelance Generative Ai Prompt Engineer information

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$14

$47

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How much do freelance generative ai prompt engineer jobs pay per hour?

As of Jul 18, 2026, the average hourly pay for freelance generative ai prompt engineer in the United States is $47.71, according to ZipRecruiter salary data. Most workers in this role earn between $24.28 and $61.78 per hour, depending on experience, location, and employer.

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

AspectFreelance Generative Ai Prompt EngineerFreelance Data Scientist
Required SkillsPrompt engineering, AI model understanding, creativityData analysis, statistical skills, programming
Work EnvironmentRemote, project-based, client-focusedRemote or on-site, research and analysis projects
Industry UsageAI development, content creation, chatbot designBusiness analytics, predictive modeling, data-driven decisions

While both roles are freelance and involve technical expertise, Freelance Generative Ai Prompt Engineers focus on crafting prompts for AI models, whereas Freelance Data Scientists analyze data to inform decisions. The roles overlap in technical skills but differ in their core functions and industry applications.

What cities are hiring for Freelance Generative Ai Prompt Engineer jobs? Cities with the most Freelance Generative Ai Prompt Engineer job openings:
What are the most commonly searched types of Generative Ai Prompt Engineer jobs? The most popular types of Generative Ai Prompt Engineer jobs are:
What states have the most Freelance Generative Ai Prompt Engineer jobs? States with the most job openings for Freelance Generative Ai Prompt Engineer jobs include:

Generative AI Engineer

XPath Solutions

Charlotte, NC

$60 - $72/hr

Full-time

Posted 2 days ago


Job description

Generative AI Engineer
Location

Dallas, TX or Charlotte, NC or Raleigh, NC



Role Overview

We are seeking a highly skilled Generative AI Engineer with a strong Python background to design, develop, and deploy cutting-edge AI solutions. The ideal candidate will have hands-on experience with Large Language Models (LLMs), Vision Language Models (Vision LLMs/VLMs), vLLM inference framework, prompt engineering, and modern Generative AI frameworks, along with proven expertise in building scalable AI applications for enterprise use cases.

This role focuses on developing Agentic AI systems, Retrieval-Augmented Generation (RAG), multimodal AI solutions, and high-performance LLM inference while integrating GenAI capabilities into production-grade enterprise applications.



Mission

Design and deliver scalable, production-ready Generative AI solutions leveraging modern LLMs, Vision LLMs, Agentic AI frameworks, RAG architectures, and cloud AI platforms to power intelligent enterprise applications.



Key Responsibilities
Design and implement Generative AI solutions for:
  • Text-based AI applications
  • Image-based AI applications
  • Vision Language Models (Vision LLMs)
  • Multimodal AI applications
AI Engineering
  • Develop and optimize advanced prompt engineering strategies to improve LLM performance, accuracy, and reliability.
  • Build and integrate embedding-based retrieval systems and Retrieval-Augmented Generation (RAG) pipelines.
  • Design and implement Agentic AI applications including:
    • Context management
    • Session and memory handling
    • MCP (Model Context Protocol)
    • Tool calling and workflow orchestration
  • Deploy and optimize vLLM for high-throughput, low-latency LLM inference in production environments.
  • Build scalable APIs using Python and integrate GenAI capabilities into enterprise applications and workflows.
  • Collaborate with cross-functional teams to deploy AI solutions at scale.
  • Ensure AI solutions are secure, scalable, reliable, and production-ready.


Required Qualifications
Programming
  • Strong proficiency in Python
AI / Machine Learning
  • Solid experience with AI/ML frameworks including:
    • PyTorch
    • TensorFlow
Agentic AI

Hands-on experience building multi-agent AI systems, including:

  • Session management
  • Memory handling
  • MCP (Model Context Protocol)
  • Tool integration and orchestration
Large Language Models

Practical experience with:

  • Large Language Models (LLMs)
  • Vision Language Models (Vision LLMs / VLMs)
  • Transformer architectures
  • Hugging Face ecosystem
  • vLLM for optimized LLM serving and inference
Retrieval & Search

Experience with:

  • Vector databases
  • Embeddings
  • Retrieval-Augmented Generation (RAG)
  • Semantic Search
Cloud AI Platforms

Experience with one or more:

  • AWS SageMaker
  • Azure OpenAI
  • Google Vertex AI
MLOps
  • Understanding of MLOps and LLMOps practices
  • Experience deploying scalable AI applications in production


Preferred Qualifications
  • Experience with multimodal AI systems combining text, images, and documents
  • Knowledge of AI ethics, including:
    • Bias mitigation
    • Responsible AI practices
  • Experience designing AI systems with governance, transparency, and compliance in mind
  • Experience with distributed GPU inference, model optimization, quantization, and high-performance AI serving
  • Familiarity with frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, or AutoGen