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Freelance Retrieval Augmented Generation Jobs (NOW HIRING)

CX DATA Labs

Python Software Engineer

Austin, TX · On-site

Develop Retrieval-Augmented Generation (RAG) solutions and AI workflows. Work with Large Language Models (LLMs) such as OpenAI, Azure OpenAI, or similar platforms. Collaborate with product managers ...

Prophecy Technologies

AI/ML Engineer

Plano, TX · On-site

$109K - $131K/yr

Fine-tune foundation models and implement Retrieval-Augmented Generation (RAG) architectures. * Develop REST APIs and microservices using FastAPI, Flask, or similar frameworks to expose AI models.

System One

GenAI Context Engineer

Pittsburgh, PA · On-site

Design and implement enterprise Retrieval Augmented Generation (RAG) architectures for GenAI platforms and applications. * Build and optimize semantic retrieval pipelines, vector search ...

System One

GenAI Context Engineer

Pittsburgh, PA · On-site

The role focuses on Retrieval Augmented Generation (RAG), semantic search, vector databases, metadata engineering, and enterprise knowledge orchestration to deliver secure, accurate, and context ...

System One

GenAI Context Engineer

Pittsburgh, PA · On-site

Design and implement enterprise Retrieval Augmented Generation (RAG) architectures for GenAI platforms and applications. * Build and optimize semantic retrieval pipelines, vector search ...

System One

GenAI Context Engineer

Pittsburgh, PA · On-site

Design and implement enterprise Retrieval Augmented Generation (RAG) architectures for GenAI platforms and applications. * Build and optimize semantic retrieval pipelines, vector search ...

cloudingest inc

Applied AI Specialist

Dallas, TX · On-site

Skilled in Retrieval-Augmented Generation (RAG), FAISS, vector databases, Transformers, BERT, Hugging Face. Frameworks & APIs: Strong with LangChain framework, REST APIs, Git, CI/CD, Kubernetes.

New

Berriehill Research

Senior AI Technologist

Albuquerque, NM · On-site +1

$50.50 - $65/hr

Working closely with business units, engineers, and functional teams, you will leverage applied AI technologies including large language models (LLMs), retrieval-augmented generation (RAG), AI agents ...

Bridge Flair LLC

AI Engineer Only on W2 USC

Malvern, PA · On-site

Develop Retrieval-Augmented Generation (RAG) pipelines using vector databases. * Create AI agents and workflow automation solutions. * Fine-tune, evaluate, and optimize AI models for performance and ...

Berriehill Research

Senior AI Technologist

Raleigh, NC · On-site +1

$48.75 - $63/hr

Working closely with business units, engineers, and functional teams, you will leverage applied AI technologies including large language models (LLMs), retrieval-augmented generation (RAG), AI agents ...

Merican

Full Stack AI Engineer (Generative AI)

Design and implement Retrieval-Augmented Generation (RAG) architectures using enterprise data sources. * Integrate AI capabilities into existing Java, .NET, or Node.js enterprise applications.

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

As of Jul 30, 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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Freelance Retrieval Augmented Generation jobs near you
Infographic showing various Freelance Retrieval Augmented Generation job openings in the United States as of July 2026, with employment types broken down into 91% Full Time, 6% Part Time, and 3% Contract. Highlights an 76% Physical, 4% Hybrid, and 20% Remote job distribution, with an average salary of $47,772 per year, or $23 per hour.

Senior AI Engineer - LLM Systems & RAG Optimization

Texas Sports Academy

Remote

Contractor

Re-posted 28 days ago

Job description

Texas Sports Academy is on the lookout for a Senior AI Engineer specializing in LLM (Large Language Model) Systems and RAG (Retrieval-Augmented Generation) Optimization. As we continue to push the boundaries of sports technology, your role will be pivotal in developing and optimizing AI-driven solutions that enhance our offerings for athletes and coaches. You will be responsible for designing, developing, and fine-tuning LLM systems that can offer personalized insights and performance recommendations based on data-driven analysis. Your expertise in retrieval-augmented generation will enable the integration of comprehensive data sources, empowering our systems to deliver high-quality, context-aware content and responses. You will work collaboratively with data scientists, software engineers, and domain experts to implement scalable AI solutions that drive innovation in our training programs. If you are passionate about harnessing the power of AI to transform the sports industry and have a strong foundation in NLP and machine learning, this is the perfect opportunity for you to make an impact.
Responsibilities
  • Design and implement LLM systems tailored to the needs of athletes and coaches.
  • Optimize retrieval-augmented generation processes to improve the quality and relevance of AI-generated content.
  • Collaborate with cross-functional teams to define AI strategies and ensure alignment with business goals.
  • Conduct research on cutting-edge AI methodologies and integrate them into existing systems.
  • Monitor and evaluate system performance, making data-driven adjustments as necessary.
  • Mentor junior team members and help cultivate a culture of innovation within the department.
  • Document system architecture, processes, and best practices for future reference and team knowledge sharing.

Requirements
  • Master's degree or Ph.D. in Computer Science, Artificial Intelligence, or a related field.
  • Extensive experience with Large Language Models (LLMs) and retrieval-augmented generation systems.
  • Proficient in programming languages such as Python, with a strong understanding of data structures and algorithms.
  • Familiarity with AI/machine learning frameworks (e.g., TensorFlow, PyTorch) and NLP libraries.
  • Experience with optimizing AI models for efficiency and performance.
  • Strong analytical and problem-solving skills with the ability to work effectively in a fast-paced environment.
  • Exceptional communication skills to articulate complex concepts to stakeholders and team members.

Apply