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Rag Developer Jobs in Miami, FL (NOW HIRING)

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.

Applied AI Engineer

Sunrise, FL · On-site

$50 - $55/hr

Experience with LangGraph, RAG, or MCP style integrations. * Experience with generative AI and prompt engineering. * Experience in continuous integration/continuous deployment pipelines and ...

New

The Engineering Manager will lead high-performing teams to deliver scalable software solutions for ... RAG) pipelines -- that improve how customers discover, book, and engage with cruise experiences ...

Experience building RAG systems, Prompt engineering, Data processing * Knowledge on AI Best practices, Evaluation techniques and Quality control strategies. * Experience with Structured and ...

... developer platforms that engineering teams depend on - including design systems, front-end ... Experience with LangGraph, RAG, or MCP-style integrations * Hands-on experience with generative AI ...

Senior Agentic (AI) Engineer

Miami, FL · On-site +1

$99K - $137K/yr

Strong RAG fundamentals chunking, embeddings, hybrid retrieval, reranking, grounding - and judgment ... Solid systems engineering instincts APIs, async patterns, queues, databases, distributed system ...

Apply modern agent architecture patterns including RAG, tool use, orchestration, memory, and ... Establish engineering standards and best practices for agentic systems, including observability ...

Senior Agentic (AI) Engineer

Miami, FL · Remote

$107K - $146K/yr

Strong RAG fundamentals chunking, embeddings, hybrid retrieval, reranking, grounding -- and ... Solid systems engineering instincts APIs, async patterns, queues, databases, distributed system ...

Implement LLM application patterns including RAG, document ingestion/chunking, embeddings, vector ... DevOps/DevSecOps experience (CI/CD, IaC such as Terraform/CloudFormation, Docker/Kubernetes ...

The Analyst, AI Engineering is an offshore technical role that supports WAI's internal AI ... Build and support retrieval-augmented generation (RAG), embeddings, vector search, document ...

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Rag Developer information

What is the difference between Rag Developer vs Textile Technician?

AspectRag DeveloperTextile Technician
CredentialsTypically requires a diploma or degree in textiles or related fieldRequires similar qualifications, often with additional certifications in textile testing
Work EnvironmentFactories, textile mills, production plantsLaboratories, quality control departments, manufacturing facilities
Industry UsageUsed in textile manufacturing to develop and process rags for reuse or recyclingInvolved in testing, quality assurance, and technical support in textile production

Both Rag Developers and Textile Technicians work within the textile industry, often in manufacturing settings. Rag Developers focus on creating and processing recycled rags, while Textile Technicians handle testing and quality control. The roles share similar educational backgrounds and work environments, but their specific responsibilities differ based on their focus within textile production.

What are popular job titles related to Rag Developer jobs in Miami, FL? For Rag Developer jobs in Miami, FL, the most frequently searched job titles are:
What cities near Miami, FL are hiring for Rag Developer jobs? Cities near Miami, FL with the most Rag Developer job openings:

Gen AI Engineer - Sunrise, FL - Contract Opportunity

Zodiac Solutions

Sunrise, FL • On-site

Contractor

Re-posted 19 days ago


Job description

Role: Gen AI Engineer

Location: Sunrise, FL (Onsite/Hybrid as per client requirement)
Duration: Long-Term Contract
Required Skills: Python, GenAI, LLM, LangChain, LangGraph, RAG.


Experience: 6+ Years

Job Description:

  • Design and develop AI-powered applications using Python and modern GenAI frameworks.
  • Build and optimize LLM-based solutions using LangChain and LangGraph.
  • Develop RAG pipelines by integrating vector databases and enterprise knowledge sources.
  • 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.
  • Experience developing and deploying AI applications in cloud environments (AWS, Azure, or GCP).
  • Strong understanding of REST APIs, microservices, and scalable application architecture.
  • Familiarity with Git, CI/CD pipelines, and Agile methodologies.