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Freelance Retrieval Augmented Generation Jobs in Florida

CYNET SYSTEMS

DOTNET AI Architect

Orlando, FL · On-site

$47 - $52/hr

Understanding of Retrieval-Augmented Generation (RAG) concepts and architectures. * Experience working with unstructured data, document repositories, and content processing solutions. * Knowledge of ...

PODS

Engineer IV - Applied AI

Clearwater, FL · On-site

Leverages existing large language models (LLMs), retrieval-augmented generation (RAG) architectures, agentic workflows, data platforms, and software engineering practices to develop scalable ...

Vultus Inc

AI/ML Engineer

Miami, FL · On-site +1

$120K - $150K/yr

Develop Retrieval-Augmented Generation (RAG) pipelines. * Work with vector databases for semantic search applications. * Perform data preprocessing, feature engineering, and model evaluation.

Luma Financial Technologies, LLC

AI/ML Engineer

Miami, FL · On-site

$100 - $130/hr

Utilize Retrieval Augmented Generation (RAG) techniques to improve data retrieval and decision‑making processes. * MLOps Integration (Plus): * Champion MLOps best practices to streamline the ...

New

Deloitte

Oracle Gen AI Manager

Miami, FL · On-site

... retrieval-augmented generation pipelines, and enterprise platform integrations • Define and enforce governance, security, compliance, and architecture standards for artificial intelligence and ...

Tror AI for everyone

AI Engineer

Lake Mary, FL · On-site

Retrieval-Augmented generation (RAG) * Document Ingestion and preprocessing * Chunking Strategies (semantic, recursive, sliding window) * Embeddings * Vector database - pgvector * Hybrid search ...

Virtusa

Python/Pyspark Developer

Tampa, FL · On-site

$47.50 - $65.50/hr

Lead the design, development, and deployment of Python and Generative AI solutions, including sophisticated Retrieval-Augmented Generation (RAG) architectures and conversational AI agents using ...

Virtusa

Data engineer

Tampa, FL · On-site

$108K - $129K/yr

Lead the design, development, and deployment of Python and Generative AI solutions, including sophisticated Retrieval-Augmented Generation (RAG) architectures and conversational AI agents using ...

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Freelance Retrieval Augmented Generation information

What is a freelance retrieval augmented generation 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.

What are the key skills and qualifications needed to thrive as a freelance retrieval augmented generation specialist?

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.

How does a freelance retrieval augmented generation specialist 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.

What are the most commonly searched types of Retrieval Augmented Generation jobs in Florida?

The most popular types of Retrieval Augmented Generation jobs in Florida are:

What are popular job titles related to Freelance Retrieval Augmented Generation jobs in Florida?

For Freelance Retrieval Augmented Generation jobs in Florida, the most frequently searched job titles are:

What job categories do people searching Freelance Retrieval Augmented Generation jobs in Florida look for?

The top searched job categories for Freelance Retrieval Augmented Generation jobs in Florida are:

What cities in Florida are hiring for Freelance Retrieval Augmented Generation jobs?

Cities in Florida with the most Freelance Retrieval Augmented Generation job openings:

Freelance Retrieval Augmented Generation jobs near you
Infographic showing various Freelance Retrieval Augmented Generation job openings in Florida as of August 2026, with employment types broken down into 33% Internship, 33% Full Time, and 34% Contract. Highlights an 67% In-person, and 33% Remote job distribution.

Information Technology_USA - USA_Developer

SysMind Tech

Tampa, FL • On-site

Contractor

Re-posted 17 days ago

Job description

**Please strictly adhere to the following resume naming convention:
ALL CAPS, NO SPACES B/T UNDERSCORES
PTN_US_GBAMSREQID_CandidateBeelineID
i.e. PTN_US_9999999_SKIPJOHNSON0413
Bill Rate: market rate/hr
GBaMS ReqID: 10585280
MSP Owner: Tory Robinson
Location: Tampa, FL - 100% Onsite
Duration: 6 + months
AI Lead/Solution Architect
Job Summary
As a Solution Architect with a focus on AI-driven intelligent systems, you will lead the design, development, and
deployment of advanced NLP and cognitive search solutions using Python, Lang chain, LangGraph,
Retrieval-Augmented Generation (RAG), and Agentic AI models.
Key Responsibilities
• Design and architect scalable, maintainable AI solutions that integrate Lang chain, LangGraph, and RAG
methodologies to enhance knowledge discovery and conversational AI capabilities.
• Lead development efforts using Python to prototype and productionize AI agents and workflows.
• Collaborate with data engineering and DevOps teams to implement data pipelines and model deployment
strategies.
• Develop and optimize RAG systems combining vector search, knowledge graphs, and LLMs to provide
contextual and accurate responses.
• Architect agentic AI systems that perform autonomous tasks by chaining actions, managing states, and
integrating external APIs.
• Provide technical leadership and architecture guidance for AI and NLP projects.
• Evaluate emerging AI technologies and frameworks to continuously improve solution design.
• Create comprehensive technical documentation and architecture diagrams to facilitate knowledge transfer.
• Ensure solutions meet security, compliance, and performance standards.
Required Skills and Qualifications
. • Strong proficiency in Python, with experience in backend or AI service development.
• Hands-on experience with Lang chain and/or LangGraph frameworks.
• Deep understanding of Retrieval-Augmented Generation (RAG) systems and techniques.
• Experience designing and implementing agentic AI architectures, autonomous workflows, or
multi-agent systems.
• Familiarity with knowledge graphs, vector search engines (e.g., FAISS, Pinecone, We aviate),
and LLM integration.
• Solid understanding of NLP concepts, transformer models, and prompt engineering.
• Ability to translate complex business requirements into scalable AI solutions.
• Experience with cloud platforms (AWS, GCP, Azure) and container orchestration (Docker,
• Kubernetes).
• Strong communication skills and ability to collaborate across multidisciplinary teams
Role Descriptions: Job SummaryAs a Solution Architect with a focus on AI-driven intelligent systems| you will lead the design| development| and deployment of advanced NLP and cognitive search solutions using Python| Langchain| LangGraph| Retrieval-Augmented Generation (RAG)| and Agentic AI models.Key ResponsibilitiesDesign and architect scalable| maintainable AI solutions that integrate Langchain| LangGraph| and RAG methodologies to enhance knowledge discovery and conversational AI capabilities.Lead development efforts using Python to prototype and productionize AI agents and workflows.Collaborate with data engineering and DevOps teams to implement data pipelines and model deployment strategies.Develop and optimize RAG systems combining vector search| knowledge graphs| and LLMs to provide contextual and accurate responses.Architect agentic AI systems that perform autonomous tasks by chaining actions| managing states| and integrating external APIs.Provide technical leadership and architecture guidance for AI and NLP projects.Evaluate emerging AI technologies and frameworks to continuously improve solution design.Create comprehensive technical dJob SummaryAs a Solution Architect with a focus on AI-driven intelligent systems| you will lead the design| development| and deployment of advanced NLP and cognitive search solutions using Python| Langchain| LangGraph| Retrieval-Augmented Generation (RAG)| and Agentic AI models.Key ResponsibilitiesDesign and architect scalable| maintainable AI solutions that integrate Langchain| LangGraph| and RAG methodologies to enhance knowledge discovery and conversational AI capabilities.Lead development efforts using Python to prototype and productionize AI agents and workflows.Collaborate with data engineering and DevOps teams to implement data pipelines and model deployment strategies.Develop and optimize RAG systems combining vector search| knowledge graphs| and LLMs to provide contextual and accurate responses.Architect ageocumentation and architecture diagrams to facilitate knowledge transfer.Ensure solutions meet security| compliance| and performance standards..Required Skills and Qualifications. Strong proficiency in Python| with experience in backend or AI service development.Hands-on experience with Langchain andor LangGraph frameworks.Deep understanding of Retrieval-Augmented Generation (RAG) systems and techniques.Experience designing and implementing agentic AI architectures| autonomous workflows| or multi-agent systems.Familiarity with knowledge graphs| vector search engines (e.g.| FAISS| Pinecone| Weaviate)| and LLM integration.Solid understanding of NLP concepts| transformer models| and prompt engineering.Ability to translate complex business requirements into scalable AI solutions.Experience with cloud platforms (AWS| GCP| Azure) and container orchestration (Docker| Kubernetes).Strong communication skills and ability to collaborate across multidisciplinary teams
Essential Skills: Job SummaryAs a Solution Architect with a focus on AI-driven intelligent systems| you will lead the design| development| and deployment of advanced NLP and cognitive search solutions using Python| Langchain| LangGraph| Retrieval-Augmented Generation (RAG)| and Agentic AI models.Key ResponsibilitiesDesign and architect scalable| maintainable AI solutions that integrate Langchain| LangGraph| and RAG methodologies to enhance knowledge discovery and conversational AI capabilities.Lead development efforts using Python to prototype and productionize AI agents and workflows.Collaborate with data engineering and DevOps teams to implement data pipelines and model deployment strategies.Develop and optimize RAG systems combining vector search| knowledge graphs| and LLMs to provide contextual and accurate responses.Architect agentic AI systems that perform autonomous tasks by chaining actions| managing states| and integrating external APIs.Provide technical leadership and architecture guidance for AI and NLP projects.Ev

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