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Freelance Retrieval Augmented Generation Jobs (NOW HIRING)

Experience building Retrieval-Augmented Generation (RAG) systems and production-grade AI applications is highly desirable. Key Responsibilities * Design, develop, and deploy machine learning and ...

Implement RAG (Retrieval Augmented Generation) patterns using requirements, user stories, APIs, configurations, and test repositories, leverage embeddings and vector search where applicable. Apply ...

GPT, Claude • Prompt Engineering • RAG (Retrieval Augmented Generation) • AWS Cloud Good to Have • Data Structures & Algorithms • OOP and modular design • CI/CD pipelines • Postman ...

Closure Technologies is seeking a AI/ML Engineer who will Implement and maintain Retrieval-Augmented Generation (RAG) pipelines and integrate Large Language Models (LLMs) into applications, supported ...

Additionally, experience in building Retrieval-Augmented Generation (RAG) pipelines for search and chat applications is highly desired. Key Responsibilities: * Develop and optimize NLP models for ...

The ideal candidate will have a strong background in investment banking, hands-on experience with Microsoft Azure OpenAI, and expertise in Retrieval-Augmented Generation (RAG). Key Responsibilities:

GPT, Claude • Prompt Engineering • RAG (Retrieval Augmented Generation) • AWS Cloud • Strong architectural and hands on GenAI expertise • Experience with enterprise automation and testing ...

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How much do freelance retrieval augmented generation jobs pay per hour?

As of Jun 14, 2026, the average hourly pay for freelance retrieval augmented generation in the United States is $22.97, according to ZipRecruiter salary data. Most workers in this role earn between $18.75 and $18.75 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Freelance Retrieval Augmented Generation Specialist, and why are they important?

To thrive as a Freelance Retrieval Augmented Generation (RAG) Specialist, you need expertise in natural language processing, information retrieval, and machine learning, typically supported by a degree in computer science or related fields. Proficiency with frameworks like Hugging Face Transformers, vector databases (e.g., FAISS, Pinecone), and cloud platforms is often required. Strong problem-solving, effective communication, and adaptability set standout professionals apart in this role. These skills ensure the development and fine-tuning of high-performance RAG systems that deliver accurate, contextually relevant results for clients.

What is a Freelance Retrieval Augmented Generation (RAG) specialist?

A Freelance Retrieval Augmented Generation (RAG) specialist is an independent professional who designs, develops, and implements AI systems that combine retrieval-based methods with generative models. RAG specialists help organizations enhance their applications by integrating large language models (LLMs) with external data sources, allowing the AI to access and utilize up-to-date information beyond its training data. Their work involves tasks such as building pipelines for document indexing and retrieval, fine-tuning models, and optimizing the integration for accuracy and efficiency. Freelance RAG specialists typically work on a contract basis, offering flexibility and expertise for businesses that need advanced AI solutions.

How do Freelance Retrieval Augmented Generation specialists typically collaborate with client teams during a project?

Freelance Retrieval Augmented Generation (RAG) specialists often work closely with client data scientists, engineers, and project managers to understand business requirements and integrate RAG systems into existing workflows. Communication is usually handled through regular virtual meetings, shared documentation, and sometimes real-time collaboration tools. Freelancers are expected to deliver modular, well-documented solutions and provide guidance on optimizing retrieval pipelines or fine-tuning models. This collaborative dynamic ensures that RAG implementations are aligned with client goals and technical standards, while also allowing freelancers to contribute innovative solutions based on their expertise.
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Infographic showing various Freelance Retrieval Augmented Generation job openings in the United States as of June 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 100% In-person job distribution, with an average salary of $47,772 per year, or $23 per hour.

Python / Generative AI Engineer

Prophecy Technologies

Los Angeles, CA • On-site

Full-time

Posted 16 days ago


Job description

JOB SUMMARY
The Python / Generative AI Engineer will design, develop, and implement AI-driven applications leveraging Generative AI technologies. The role focuses on building scalable AI solutions using Python, developing Retrieval-Augmented Generation (RAG) systems, and integrating AI models within cloud environments. The engineer will work closely with data scientists, engineers, and DevOps teams to implement GenAI solutions, optimize prompts, and deploy AI applications using modern cloud and container technologies.
Location
Los Angeles, CA / Irvine, CA (Hybrid)
Experience
5+ Years
Key Responsibilities
• Design and develop scalable applications using Python and SQL.
• Implement Generative AI solutions leveraging modern AI frameworks and tools.
• Build and maintain Retrieval-Augmented Generation (RAG) systems for AI-powered applications.
• Develop prompt engineering strategies to improve GenAI model outputs.
• Integrate AI solutions with cloud platforms and enterprise systems.
• Deploy and manage AI workloads using AWS, Docker, and DevOps pipelines.
• Collaborate with cross-functional teams to translate business problems into AI-driven solutions.
• Optimize AI workflows and ensure performance, reliability, and scalability.
• Implement and manage the Generative AI lifecycle including development, testing, deployment, and monitoring.
• Troubleshoot and resolve issues related to AI model integration and deployment.
Required Skills & Experience
• Minimum 5+ years of strong hands-on experience in Python development.
• Strong proficiency in SQL for data processing and analysis.
• Hands-on experience in Generative AI development using Python.
• Experience building Retrieval-Augmented Generation (RAG) based AI systems.
• Strong knowledge of prompt engineering and GenAI model interaction.
• Experience with AWS cloud services.
• Experience with containerization technologies such as Docker.
• Familiarity with DevOps practices and CI/CD pipelines.
• Strong analytical thinking, problem-solving, and critical reasoning skills.
• Ability to work independently with strong ownership and accountability.
Competencies
• Python Development
• Generative AI Development
• Retrieval-Augmented Generation (RAG)
• Prompt Engineering
• Cloud Computing (AWS)
• DevOps & Containerization
• SQL & Data Processing
Preferred Skills
• Experience using LangChain for building AI agents and GenAI workflows.
• Experience designing enterprise-level AI applications.
• Exposure to AI/ML model lifecycle management and deployment frameworks.