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Overnight Retrieval Augmented Generation Jobs in Florida

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

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 ...

Design and build retrieval-augmented generation (RAG) solutions, including embedding, vector search, and orchestration, and select the models and services behind them. * Build evaluation and ...

New

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

Design and build retrieval-augmented generation (RAG) solutions, including embedding, vector search, and orchestration, and select the models and services behind them. * Build evaluation and ...

New

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 ...

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 ...

AI Lead (Generative AI)

Tampa, FL · On-site

$127K - $156K/yr

The ideal candidate will have hands-on experience with Large Language Models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), Multi-Agent systems, Python, AI workflow orchestration ...

Knowledge of Retrieval-Augmented Generation (RAG) * Familiarity with Agentic AI frameworks * Natural Language Processing (NLP) * NoSQL GraphDB Qualifications: * 4-6 years of experience in AI ...

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Overnight Retrieval Augmented Generation information

What is the difference between Overnight Retrieval Augmented Generation vs Data Scientist?

AspectOvernight Retrieval Augmented GenerationData Scientist
CredentialsTypically requires knowledge of AI, NLP, and data retrieval techniquesRequires degrees in data science, statistics, or related fields
Work EnvironmentOften in AI research labs, tech companies, or startups focusing on NLP modelsIn corporate, research, or consulting settings analyzing data and building models
Industry UsagePrimarily in AI, machine learning, and NLP industriesAcross finance, healthcare, tech, and other sectors

Overnight Retrieval Augmented Generation focuses on developing AI models that combine retrieval techniques with generative AI, often working overnight to update or improve models. Data Scientists analyze data, build predictive models, and interpret results across various industries. While both roles involve data and AI, Retrieval Augmented Generation specialists focus on model training and NLP innovations, whereas Data Scientists handle broader data analysis and modeling tasks.

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 Overnight Retrieval Augmented Generation jobs in Florida?

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

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

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

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

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

Infographic showing various Overnight Retrieval Augmented Generation job openings in Florida as of July 2026, with employment types broken down into 88% Full Time, 10% Part Time, and 2% Contract. Highlights an 77% Physical, 3% Hybrid, and 20% Remote job distribution.

Information Technology_USA - USA_Developer

SysMind Tech

Tampa, FL • On-site

Contractor

Re-posted yesterday


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