1

Rag Developer Jobs in Boca Raton, FL (NOW HIRING)

AI Engineer

Sunrise, FL ยท On-site

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

AI Engineer

Sunrise, FL ยท On-site

... 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 ...

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

DevOpsEngineer

Wellington, FL ยท On-site

$49.25 - $67.50/hr

... E to deploy, operate, and harden the AI systems that support corrections operations and intelligence analysis. Our data scientists build LLM-powered agents, RAG pipelines, and ontology-driven ...

... as RAG. This role works closely with AI Engineers, solution architects, and platform teams to ... ensure data infrastructure is production-ready, secure, and aligned with GEI standards. Essential ...

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 ...

Data Engineer

West Palm Beach, FL ยท On-site

$110K - $133K/yr

... as RAG. This role works closely with AI Engineers, solution architects, and platform teams to ... ensure data infrastructure is production-ready, secure, and aligned with GEI standards. Essential ...

Senior Data & AI Engineer

Boca Raton, FL

$100K - $136K/yr

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

Senior Data & AI Engineer

Fort Lauderdale, FL ยท On-site

$101K - $137K/yr

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

About the role As an Applied AI Engineer, you will drive the design, build, and deployment of next ... Develop and optimize Retrieval-Augmented Generation (RAG) systems, including embeddings, vector ...

We're looking for a Software Engineer to scale MySQL performance, optimize product functionality ... Lead development of new AI/ML-driven product features (vector search, RAG, embeddings, automation ...

next page

Showing results 1-20

Rag Developer information

What engineers make $500,000?

Senior engineers in specialized fields such as software engineering, data engineering, or engineering management can earn $500,000 or more annually, especially with extensive experience, advanced skills, and in high-demand industries like technology or finance. Compensation often includes base salary, bonuses, and stock options, particularly at large tech companies or startups with significant growth potential.

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 does a RAG engineer do?

A RAG (Red, Amber, Green) engineer develops and maintains systems that use RAG status indicators to monitor project or system health. They often work with data visualization tools, automate status reporting, and analyze performance metrics to support decision-making. Strong skills in data analysis, programming, and understanding of project management are typically required.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-paying position in artificial intelligence, such as senior machine learning engineer, AI research director, or executive roles like AI CTO. These roles often require advanced skills in programming, data analysis, and experience with AI frameworks, and they may involve leadership responsibilities or specialized expertise in cutting-edge AI technologies.

Which 3 jobs will survive AI?

For a Rag Developer, roles that require complex manual craftsmanship, creative problem-solving, and specialized knowledge are more likely to persist despite AI advancements. Jobs involving intricate textile design, custom tailoring, and quality inspection rely on human skills and judgment that AI cannot fully replicate. Developing expertise in these areas, along with staying updated on industry tools, can help ensure job security.
What are popular job titles related to Rag Developer jobs in Boca Raton, FL? For Rag Developer jobs in Boca Raton, FL, the most frequently searched job titles are:
What job categories do people searching Rag Developer jobs in Boca Raton, FL look for? The top searched job categories for Rag Developer jobs in Boca Raton, FL are:
What cities near Boca Raton, FL are hiring for Rag Developer jobs? Cities near Boca Raton, FL with the most Rag Developer job openings:
AI Retrieval & Relevance Engineer (RAG / Hybrid Search)

AI Retrieval & Relevance Engineer (RAG / Hybrid Search)

iBusiness Funding LLC

Fort Lauderdale, FL โ€ข Hybrid

Full-time

Re-posted 18 days ago


Job description

AboutiBusiness.ai

iBusiness.ai is a leading financial technology company helping banks, credit unions, and lenders modernize lending operations through secure AI, automation, and enterprise software. In the last decade the company's platforms have grown into supporting more than 50 financial institutions and havefacilitatedover$11 billionin lending volume.

As apioneerinsecureAI, automation, and AI software development,webuild infrastructure and platforms that empower teams to modernize processes and work more efficiently without sacrificing compliance or security. Our workflow, verticalized, and point solutions enableseamless digital transformation, giving organizations of all sizes the tools they need to compete, innovate, and grow.

Join us and be part of a team that's building solutions designed to help businesses thrive!


PositionDescription


WeareseekinganexperiencedAIRetrieval&RelevanceEngineertoarchitect,implement,andoptimizeretrieval-augmentedgeneration(RAG)andhybridsearchsystemsthatprovideaccurate,groundedcontexttoLLMsandAIagents.Thisroleownstheretrievalpipelineend-to-end-fromindexingstrategyandcandidategenerationthroughranking/rerankingandevaluation-toensureoursystemsefficientlyretrieve,contextualize,andsupportaccurateoutputsacrossbusinessapplications.YouwillcollaboratecloselywithKnowledgeRepresentationengineeringtoleverageknowledgegraphsandsemanticsignalsinretrieval.


MajorAreasofResponsibility

RAGArchitecture&HybridRetrieval


  • Architect,implement,andoptimizeRAGworkflowsintegratingLLMswithretrievalmechanisms(vectorsearch,Elasticsearch,FAISS,Weaviate).
  • Implementandoptimizedense/sparse/hybridretrievalstrategies,rankingalgorithms,reranking,andqueryrewritingtomaximizerelevanceandaccuracy.
  • Integrategraph-awareretrievalpatterns(entity-centricexpansion,metadatafilters,constrainedtraversal)usingsignalsdefinedbyKnowledgeRepresentation.
  • Indexing,Ingestion-to-RetrievalPipelines(RetrievalView)
  • Designandmaintainscalablepipelinesforindexingandretrievalreadiness:chunking,embedding,metadataenrichment,indexrefreshandbackfills.
  • Ensure reliable retrieval across structured and unstructured data with appropriate filtering, boosting, and context packaging strategies.


TrainingDataOperations(Retrieval&Evals)


  • Orchestrateandscaleretrieval-relatedtraining/evaluationdataoperations,including:
  • querysets/goldendatasets,relevancejudgments,regressionsuitesandbenchmarks
  • lineageandversioningofevaldatasets


Evaluation,Observability,andPerformance


  • Defineandrunretrievalevaluation:recall@k,nDCG/MRR,contextprecision,andgroundedness/citationsuccessmetrics.
  • Instrumenttelemetryanddashboardsforretrievalquality,drift,latency(p95/p99),andcost.
  • Optimizeperformanceandreliability:caching,ratelimiting,tieredretrieval,fallbacks.


AgentTooling&AddressableServices


  • Designandbuildaddressableretrievalservices/toolsthatcanbeinvokedbyLLMsandagentstoorchestrateworkflows(queryendpoints,retrievaltools,contextassemblyservices).


Collaboration&Documentation


  • WorkwithKnowledgeRepresentationengineeringtoalignonentity/metadatacontractsandprovenancesignalsusedinretrieval.
  • Maintaincleardocumentationofretrievalmodels,pipelines,evals,andrunbooks.
  • Evaluateandintegratenewtechnologiesandresearchininformationretrieval,RAG,andvectorsearch.


RequiredKnowledge,Skills,andAbilities


  • Bachelor'sorMaster'sdegreeinComputerScience,DataScience,MachineLearning,orrelatedfield(orequivalentexperience).
  • Provenexperiencedesigningandtuninginformationretrievalsystems,vectorsearch,andRAGframeworks.
  • Strongknowledgeofvectorandhybridsearchtechnologies(e.g.,FAISS,Weaviate,Elasticsearch,Milvus/Pineconeequivalents).
  • ProficiencyinPythonandfamiliaritywithMLtooling(PyTorch/TensorFlowhelpful,especiallyforrerankers).
  • Familiaritywithdistributedprocessing/orchestrationtools(e.g.,Spark,Airflow,Kubeflow)asneededforindexingandevalpipelines.
  • Stronganalyticalandcommunicationskills;abletocollaboratecross-functionally.


NiceToHaves


  • Experiencewithrerankers/learning-to-rank,queryunderstanding,andrelevancetuning.
  • ExperiencewithLLMfine-tuning,promptengineering,andRAGoptimization.
  • Familiaritywithagenticsystemsandmulti-stepretrieval(iterativeretrieval,tool-usepatterns).
  • Cloudandscalablestorage/indexingplatformexperience.


PrimaryOwnership(Whatsuccesslookslike)


  • Retrievaldelivershighrecall+highprecisioncontextwithstronggroundingandcitations.
  • Stableevaluationandregressiongating;nosurpriserelevanceregressions.
  • Meetslatency/costtargetswhileimprovingansweraccuracy.


Conclusion:

Thisjobdescriptionisintendedtoconveyinformationessentialtounderstandingthescopeofthejobandthegeneralnatureandlevelofworkperformedbyjobholderswithinthisjob.Thisjobdescriptionisnotintendedtobeanexhaustivelistofqualifications,skills,efforts,duties,responsibilities,orworkingconditionsassociatedwiththeposition.

Thecompanyisanequalopportunityemployerandwillconsiderallapplicationswithoutregardtorace,sex,age,color,religion,nationalorigin,veteranstatus,disability,geneticinformation,oranyothercharacteristicprotectedbylaw.