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Freelance Retrieval Augmented Generation Jobs (NOW HIRING)

Futran Tech Solutions Pvt. Ltd.

Data Scientist

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 ...

Compunnel

Senior AI Engineer Agentic Solutions

Conroe, TX · On-site

$47.25 - $61/hr

This role focuses on building production-grade AI systems from the ground up, leveraging large language models (LLMs), agent orchestration frameworks, retrieval-augmented generation (RAG), and ...

Purple Drive Technologies

Senior AI Engineer

Hartford, CT · On-site

$55.75 - $71.75/hr

Mandatory Skills Google CCAI (Contact Center AI) Google Vertex AI RAG (Retrieval Augmented Generation) AI/ML Google GCP MLOps Healthcare Payer Cloud AI Platform Summary As an AI engineer, you will be ...

Closure Technologies

AI/ML Engineer

Mclean, VA · On-site

Job Summary : Closure Technologies is seeking an AI/ML Engineer who will implement and maintain Retrieval-Augmented Generation (RAG) pipelines and integrate Large Language Models (LLMs) into ...

CYNET SYSTEMS

Senior AI Engineer - Privacy

Bellevue, WA · On-site

$70 - $75/hr

This role involves applying large language models, retrieval-augmented generation, multi-agent orchestration, and foundation model capabilities to automate and enhance privacy operations. Requirement ...

Tekshapers Inc

Generative AI/ML Engineer

New York, NY · On-site

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:

Redolent, Inc.

Sr, ML Architect

Washington, DC · On-site

Integrate with large language models (LLMs) and generative AI (GenAI) using prompt engineering, fine-tuning, and retrieval-augmented generation (RAG) techniques. * Implement MCP client and server ...

Pereview Software

AI Engineer

Dallas, TX

Develop and maintain Retrieval-Augmented Generation (RAG) architectures using vector databases and semantic search technologies * Create, test, and refine prompts, structured outputs, and evaluation ...

CYNET SYSTEMS

Java Fullstack Developer

Pittsburgh, PA · On-site

$45 - $50/hr

Knowledge of LLMs, AI agents, and Retrieval-Augmented Generation (RAG) frameworks. Responsibilities: * Design, develop, and maintain scalable microservices using Core Java and Spring Boot. * Build ...

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Freelance Retrieval Augmented Generation information

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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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Freelance Retrieval Augmented Generation jobs near you
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.

GenAI Engineer - Azure OpenAI & AWS Bedrock

Prophecy Technologies

Malvern, PA • On-site

$126K/yr

Full-time

Posted 10 hours ago

Job description

Job Summary:
We are seeking a GenAI Engineer with hands-on experience in Azure OpenAI and AWS Bedrock to design, develop, and deploy scalable Generative AI solutions. The role focuses on building Retrieval-Augmented Generation (RAG) pipelines, integrating Large Language Models (LLMs) into enterprise applications, and ensuring performance, security, and cost efficiency in AI-driven systems.
Location:
Malvern, PA - Onsite
Key Responsibilities:
  • Design, develop, and implement Retrieval-Augmented Generation (RAG) pipelines, including document ingestion, chunking, and embedding generation.
  • Configure, manage, and optimize vector databases for semantic and hybrid search performance.
  • Securely integrate Large Language Model (LLM) APIs into enterprise applications and workflows.
  • Develop and manage prompt templates and context-handling strategies to ensure consistent and accurate LLM responses.
  • Implement monitoring and logging for LLM usage, performance, latency, and cost tracking.
  • Build reusable AI components, frameworks, and SDKs to enable AI integration across multiple business use cases.

Required Skills & Experience:
  • Strong hands-on experience with Azure OpenAI services.
  • Experience working with AWS Bedrock and related AWS AI services.
  • Proficiency in Python for AI/ML and backend development.
  • Experience designing and deploying RAG architectures.
  • Knowledge of vector databases and embedding-based search solutions.
  • Experience integrating LLM APIs into applications securely.

Competencies:
  • Strong analytical and problem-solving skills.
  • Ability to design scalable and reusable AI solutions.
  • Attention to performance, security, and cost optimization.
  • Strong communication skills and ability to collaborate with cross-functional teams.

Preferred Skills:
  • Experience with hybrid cloud AI architectures (Azure + AWS).
  • Familiarity with MLOps, observability, and cost-governance practices for GenAI solutions.
  • Experience building AI SDKs or shared AI platforms.

Apply