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Freelance Generative Ai Engineer Jobs (NOW HIRING)

Aroha Technologies

Generative AI Engineer

Dallas, TX · Hybrid

Generative AI Engineer Location: Dallas, TX (Onsite 5 days/week) Employment Type: Contract Role Overview We are seeking a skilled Generative AI Engineer to design, develop, and deploy enterprise ...

New

Carlin Shayn Inc

Generative AI Engineer

Phoenix, AZ · On-site

Generative AI Engineer (Agentic AI / LLM Solutions) Location: Phoenix, AZ / New York City, NY (Hybrid/Onsite) Duration: 12+ Months Contract Interview Mode: Video Interview Position Overview We are ...

Prosum Inc.

Generative AI Engineer

Fort Worth, TX · On-site

$120K - $170K/yr

Generative AI Engineer Location: Remote (U.S.) Salary Range: $120k to $170k About the Role We are seeking a highly skilled Generative AI Engineer to lead the end-to-end delivery of production-grade ...

Prophecy Technologies

Generative AI Engineer

Tampa, FL · On-site

The role is for an AI Engineer focused on designing, developing, and implementing machine learning and AI models, particularly Generative AI applications and Agentic AI solutions. The engineer will ...

OpenDataJobs

Senior Generative AI Engineer

Potomac, MD · On-site +1

$57.25 - $73.75/hr

Our client is seeking a Senior Generative AI Engineer to drive internal initiatives and provide AI engineering support for a major federal agency. The role centers on developing cloud-native ...

OpenDataJobs

Senior Generative AI Engineer

Potomac, MD · Remote

$56.50 - $73/hr

Our client is seeking a Senior Generative AI Engineer to drive internal initiatives and provide AI engineering support for a major federal agency. The role centers on developing cloud-native ...

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

As of Jun 12, 2026, the average hourly pay for freelance generative ai 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 are the most common challenges faced by freelance Generative AI Engineers when working with clients on custom AI solutions?

Freelance Generative AI Engineers often encounter challenges such as managing client expectations regarding project timelines and the complexity of AI models, especially when clients have limited technical knowledge. Ensuring clear communication about data requirements, model capabilities, and ethical considerations is crucial for successful project delivery. Additionally, freelancers must stay up to date with rapidly evolving AI frameworks and tools while balancing multiple projects and deadlines. Building robust documentation and maintaining transparency throughout the development process can help mitigate misunderstandings and foster long-term client relationships.

What is a Freelance Generative AI Engineer?

A Freelance Generative AI Engineer is a professional who works independently to design, build, and deploy artificial intelligence models that can generate new data, such as text, images, or music. These engineers typically specialize in technologies like generative adversarial networks (GANs), large language models (LLMs), and other machine learning frameworks. They collaborate with clients or companies on a project-by-project basis, offering expertise in AI model development, fine-tuning, and integration. Being freelance, they have the flexibility to work with multiple clients across various industries, including tech, media, and entertainment.

What are the key skills and qualifications needed to thrive as a Freelance Generative AI Engineer, and why are they important?

To thrive as a Freelance Generative AI Engineer, you need a deep understanding of machine learning, neural networks, and programming languages such as Python, often supported by a degree in computer science or related field. Familiarity with frameworks like TensorFlow or PyTorch, cloud platforms, and experience with AI model deployment are typically required. Strong problem-solving abilities, adaptability, and effective communication help you collaborate with clients and address evolving project needs. These skills are crucial for developing innovative AI solutions, meeting client expectations, and staying competitive in a rapidly changing field.
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Freelance Generative Ai Engineer jobs near you
Infographic showing various Freelance Generative Ai Engineer job openings in the United States as of June 2026, with employment types broken down into 64% Full Time, and 36% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $99,230 per year, or $47.7 per hour.
Generative AI Engineer

Generative AI Engineer

Aroha Technologies

Dallas, TX • Hybrid

Other

Posted yesterday

Job description

Job Title: Generative AI Engineer
Location: Dallas, TX (Onsite 5 days/week)
Employment Type: Contract
Role Overview
We are seeking a skilled Generative AI Engineer to design, develop, and deploy enterprise-grade AI solutions using LLMs, RAG pipelines, and agentic AI systems. The ideal candidate will have hands-on experience with modern GenAI frameworks, cloud platforms, and strong software engineering fundamentals.
Key Responsibilities
  • Design and develop Generative AI applications using LLMs (OpenAI, Gemini, Claude, Llama, etc.)
  • Build and optimize RAG (Retrieval-Augmented Generation) pipelines integrating enterprise data
  • Develop AI agents / agentic systems for autonomous workflows and decision-making
  • Implement prompt engineering, embeddings, and vector search solutions
  • Build scalable APIs and microservices for AI-powered applications
  • Integrate AI models with enterprise systems (databases, APIs, data lakes)
  • Deploy solutions on AWS / Azure / Google Cloud Platform with CI/CD pipelines
  • Implement LLMOps/MLOps practices including monitoring, evaluation, and versioning
  • Ensure AI safety, governance, and hallucination mitigation
  • Collaborate with stakeholders to translate business requirements into AI solutions
Required Skills
  • Strong programming experience in Python (mandatory)
  • Hands-on experience with:
    • LangChain / LlamaIndex / Agent frameworks
    • Vector DBs (Pinecone, FAISS, Weaviate, ChromaDB)
    • RAG & embeddings
  • Knowledge of LLMs, NLP, and transformer models
  • Experience with Docker, APIs, and microservices architecture
  • Cloud experience: AWS / Azure / Google Cloud Platform
  • Understanding of MLOps / LLMOps (CI/CD, monitoring, evaluation)
Preferred Qualifications
  • Experience building production-grade GenAI or agentic systems
  • Knowledge of GraphRAG, knowledge graphs, ontology extraction
  • Exposure to Databricks / MLflow / Spark
  • Experience in fine-tuning LLMs or model optimization
Education
  • Bachelor's or Master's degree in Computer Science, AI, ML, or related field
Mandatory / Preferred Certifications (AI-Focused)
Include at least 1 2 of the following:
  • Google Cloud Professional Machine Learning Engineer
  • Microsoft Azure AI Engineer Associate
  • AWS Machine Learning Specialty
  • Databricks Generative AI Engineer Certification
  • NVIDIA Deep Learning Institute (DLI) Certifications
  • OpenAI / LLM / Prompt Engineering certifications (any recognized program)
(Certifications significantly strengthen candidacy for enterprise AI roles.)
Experience
  • 5+ years in software engineering / AI/ML
  • 2+ years in Generative AI / LLM-based solutions
Nice to Have
  • Experience with agentic AI / multi-agent systems
  • Strong understanding of AI governance & responsible AI
  • Prior experience working in onsite enterprise environments

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