... Retrieval-Augmented Generation (RAG), and Agentic AI models. Key Responsibilities • Design and architect scalable, maintainable AI solutions that integrate Lang chain, LangGraph, and RAG ...
... Retrieval-Augmented Generation (RAG), and Agentic AI models. Key Responsibilities • Design and architect scalable, maintainable AI solutions that integrate Lang chain, LangGraph, and RAG ...
AI Engineer with Python
Sunrise, FL · On-site
Implement Retrieval-Augmented Generation (RAG) pipelines and integrate Large Language Models (LLMs) * Deliver Gen AI use cases in live production environments Required Skills * Python programming ...
AI Engineer with Python
Sunrise, FL · On-site
Implement Retrieval-Augmented Generation (RAG) pipelines and integrate Large Language Models (LLMs) * Deliver Gen AI use cases in live production environments Required Skills * Python programming ...
Engineer IV - Applied AI
Clearwater, FL · On-site
$140 - $190/hr
Leverages existing large language models (LLMs), retrieval-augmented generation (RAG) architectures, agentic workflows, data platforms, and software engineering practices to develop scalable ...
Engineer IV - Applied AI
Clearwater, FL · On-site
$140 - $190/hr
Leverages existing large language models (LLMs), retrieval-augmented generation (RAG) architectures, agentic workflows, data platforms, and software engineering practices to develop scalable ...
Leverages existing large language models (LLMs), retrieval-augmented generation (RAG) architectures, agentic workflows, data platforms, and software engineering practices to develop scalable ...
Quick apply
Leverages existing large language models (LLMs), retrieval-augmented generation (RAG) architectures, agentic workflows, data platforms, and software engineering practices to develop scalable ...
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 ...
Quick apply
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 ...
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 ...
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 ...
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 ...
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 ...
Experience with prompt engineering, RAG (Retrieval-Augmented Generation), and vector databases. * Knowledge of AI model integration using APIs such as OpenAI, Anthropic, or similar platforms.
Quick apply
Experience with prompt engineering, RAG (Retrieval-Augmented Generation), and vector databases. * Knowledge of AI model integration using APIs such as OpenAI, Anthropic, or similar platforms.
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 ...
Quick apply
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 ...
IT AI Innovation Engineer
Tampa, FL · On-site
Build advanced AI workflows such as retrieval-augmented generation (RAG) pipelines, prompt chaining, contract automation, and interactive Q&A assistants for attorneys and legal support teams. • ...
IT AI Innovation Engineer
Tampa, FL · On-site
Build advanced AI workflows such as retrieval-augmented generation (RAG) pipelines, prompt chaining, contract automation, and interactive Q&A assistants for attorneys and legal support teams. • ...
Retrieval-Augmented Generation (RAG) * Vector Databases * LangChain, LlamaIndex, Semantic Kernel, or similar frameworks * Git, CI/CD, DevOps practices * Data Engineering * Data Modeling * Power BI ...
Retrieval-Augmented Generation (RAG) * Vector Databases * LangChain, LlamaIndex, Semantic Kernel, or similar frameworks * Git, CI/CD, DevOps practices * Data Engineering * Data Modeling * Power BI ...
Data engineer
$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 ...
Data engineer
$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
$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 ...
Python/Pyspark Developer
$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 ...
... and retrieval-augmented generation. * Engineering integrations between data platforms, governance, risk, and compliance workflows, and enterprise systems using application programming interfaces ...
... and retrieval-augmented generation. * Engineering integrations between data platforms, governance, risk, and compliance workflows, and enterprise systems using application programming interfaces ...
... and retrieval-augmented generation. * Engineering integrations between data platforms, governance, risk, and compliance workflows, and enterprise systems using application programming interfaces ...
... and retrieval-augmented generation. * Engineering integrations between data platforms, governance, risk, and compliance workflows, and enterprise systems using application programming interfaces ...
... and retrieval-augmented generation. * Engineering integrations between data platforms, governance, risk, and compliance workflows, and enterprise systems using application programming interfaces ...
... and retrieval-augmented generation. * Engineering integrations between data platforms, governance, risk, and compliance workflows, and enterprise systems using application programming interfaces ...
Drive the firm's adoption of AI engineering best practices, including prompt engineering, model evaluation, retrieval-augmented generation (RAG), Model Context Protocol (MCP), vector search, tool ...
Drive the firm's adoption of AI engineering best practices, including prompt engineering, model evaluation, retrieval-augmented generation (RAG), Model Context Protocol (MCP), vector search, tool ...
Drive the firm's adoption of AI engineering best practices, including prompt engineering, model evaluation, retrieval-augmented generation (RAG), Model Context Protocol (MCP), vector search, tool ...
Drive the firm's adoption of AI engineering best practices, including prompt engineering, model evaluation, retrieval-augmented generation (RAG), Model Context Protocol (MCP), vector search, tool ...
... retrieval-augmented generation, vector databases, tool calling, evaluation harnesses, prompt engineering, LLM application testing, and agent observability. - Collaborate remotely with teams and ...
Quick apply
... retrieval-augmented generation, vector databases, tool calling, evaluation harnesses, prompt engineering, LLM application testing, and agent observability. - Collaborate remotely with teams and ...
Lead delivery of Generative AI solutions utilizing Retrieval-Augmented Generation (RAG) architectures and Large Language Models (LLMs). * Coordinate activities between Government stakeholders ...
Lead delivery of Generative AI solutions utilizing Retrieval-Augmented Generation (RAG) architectures and Large Language Models (LLMs). * Coordinate activities between Government stakeholders ...
Temporary Retrieval Augmented Generation information
What is the difference between Temporary Retrieval Augmented Generation vs Data Scientist?
| Aspect | Temporary Retrieval Augmented Generation | Data Scientist |
|---|---|---|
| Required Credentials | Typically requires knowledge of AI, NLP, and some programming skills | Requires degrees in data science, statistics, or related fields, often with certifications in data analysis |
| Work Environment | Often project-based, working with AI models and large datasets in tech or research firms | Usually in corporate, research, or tech companies analyzing data to inform decisions |
| Industry Usage | Used in AI development, natural language processing, and machine learning projects | Applied across industries for data analysis, predictive modeling, and business insights |
Temporary Retrieval Augmented Generation focuses on enhancing AI models with retrieval techniques, while Data Scientists analyze data to generate insights. Both roles require technical skills but serve different purposes within the tech and data ecosystem.
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 Temporary Retrieval Augmented Generation jobs in Florida?
For Temporary Retrieval Augmented Generation jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Temporary Retrieval Augmented Generation jobs in Florida look for?
The top searched job categories for Temporary Retrieval Augmented Generation jobs in Florida are:
What cities in Florida are hiring for Temporary Retrieval Augmented Generation jobs?
Cities in Florida with the most Temporary Retrieval Augmented Generation job openings:
Information Technology_USA - USA_Developer
Tampa, FL • On-site
SysMind Tech
Contractor
Re-posted 25 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
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