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Ai Rag Jobs in Oklahoma (NOW HIRING)

ACCLiiVE

Azure Web and Mobile Developer - Tulsa, OK

Tulsa, OK · On-site

$47.75 - $59.25/hr

Experience in building AI agents and creating chunks for RAG (Retrieval-Augmented Generation). Expertise in building, packaging, and consuming .NET (NuGet) packages. Skilled in Azure Cloud services ...

Harris

Support Specialist

Kansas, OK · On-site

$65K - $75K/yr

Advanced understanding of AI agent and chatbot creation using RAG methodology to further enhance the implementation of chatbots for FA2 and Prosoft Technical phone support to customers. Learning ...

Cloudbeds

$140K - $180K/yr

Experience with MCP, vector databases, retrieval patterns, RAG architectures, or AI evaluation platforms * Comfortable working across a polyglot stack, especially contributing to or integrating with ...

Wipro Limited

DEVELOPER L4(CONTRACT)

Tulsa, OK · On-site

$60K - $135K/yr

Experience in building AI agents and creating chunks for RAG (Retrieval-Augmented Generation). Expertise in building, packaging, and consuming .NET (NuGet) packages. Skilled in Azure Cloud services ...

Gitwit Creative

Principal Software Engineer

Tulsa, OK · On-site

$190 - $230/hr

Work with foundation‑model APIs, prompt engineering, RAG, tool calling, agent workflows, and evaluate trade‑offs. * Voracious learning and sharp judgment. Understand emerging AI and apply it ...

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Ai Rag information

What is an AI RAG?

AI RAGs, or Retrieval-Augmented Generation systems, are a type of artificial intelligence that combines the power of retrieving information from large databases or documents with generating human-like text responses. This approach allows AI models to provide more accurate, up-to-date, and contextually relevant answers by referencing external data sources during the generation process. RAGs are commonly used in applications like chatbots, search engines, and customer support systems, where comprehensive and factual responses are important.

What are the key skills and qualifications needed to thrive as an AI researcher?

To thrive as an AI Researcher, you need a strong background in computer science, mathematics, and machine learning, usually with an advanced degree such as a Master's or Ph.D. Proficiency with programming languages like Python, deep learning frameworks (e.g., TensorFlow, PyTorch), and familiarity with scientific research tools is essential. Critical thinking, creativity, and effective collaboration are vital soft skills for generating novel ideas and working in multidisciplinary teams. These skills and qualities are crucial to drive innovation and solve complex problems in the rapidly evolving field of artificial intelligence.

What are common challenges faced by AI RAG engineers when integrating retrieval systems with large language models?

AI RAG engineers often encounter challenges such as ensuring seamless integration between retrieval systems and language models, maintaining low latency for real-time responses, and handling the quality and relevance of retrieved data. Additionally, tuning the system to balance retrieval accuracy with generative fluency can be complex, especially when dealing with large or unstructured datasets. Collaboration with data engineers, ML researchers, and product teams is essential to address these challenges and optimize system performance.

What is the difference between Ai Rag vs Data Analyst?

AspectAi RagData Analyst
Required CredentialsTypically a diploma or certification in AI, machine learning, or related fieldsBachelor's degree in statistics, mathematics, or related fields
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, healthcare, and various industries
Employer & Industry UsagePrimarily in AI development and researchAcross industries for data interpretation and decision-making
Common Search & ComparisonYesYes

Ai Rag and Data Analyst roles share overlapping skills in data handling and analysis, but Ai Rag focuses more on AI-specific applications and machine learning, while Data Analysts concentrate on interpreting data to inform business decisions. Both roles are vital in data-driven industries, with Ai Rag often working in AI development environments and Data Analysts supporting strategic insights across sectors.

What are popular job titles related to Ai Rag jobs in Oklahoma?

For Ai Rag jobs in Oklahoma, the most frequently searched job titles are:

What job categories do people searching Ai Rag jobs in Oklahoma look for?

The top searched job categories for Ai Rag jobs in Oklahoma are:

What cities in Oklahoma are hiring for Ai Rag jobs?

Cities in Oklahoma with the most Ai Rag job openings:

Ai Rag jobs near you
Infographic showing various Ai Rag job openings in Oklahoma as of July 2026, with employment types broken down into 79% Full Time, 19% Part Time, and 2% Contract. Highlights an 64% Physical, 3% Hybrid, and 33% Remote job distribution.

Azure Web and Mobile developers C2C jobs - Tulsa, OK (Hybrid)

Tech Mirrors

Tulsa, OK • On-site

$85 - $110/hr

Other

Posted 3 days ago

New

Job description

Role – Azure Web and Mobile developers (.NET, Azure, Blazor, Mobile Applications)
Location – Tulsa, OK – Hybrid

Mandatory – Mobile applications, Obj C/Swift experiences on current project

Must Have
  • Design, develop, and maintain scalable web and mobile applications.
  • Build and integrate secure APIs and backend services.
  • Strong hands-on experience with .NET, C# and Blazor development.
  • Experience in building AI agents and creating chunks for RAG (Retrieval-Augmented Generation).
  • Expertise in building, packaging, and consuming .NET (NuGet) packages.
  • Skilled in Azure Cloud services (App Services, Functions, Storage, Key Vault, Azure App Services, Functions, Logic Apps etc.).
  • Proficiency in SQL development and performance tuning.
  • Solid experience with Azure DevOps Pipelines for CI/CD.
  • Support UAT, QA, and Production deployments.
Should Have
  • Experience with Azure Terraform for Infrastructure as Code.
  • Objective C, Swift, Swift UI.
  • Knowledge of Azure Monitoring & Application Insights.
  • Solid understanding of secure SDLC and DevSecOps practices.
  • Experience with Azure API Management.
  • Azure AI, Databricks.
  • Azure certifications (AZ 204 / AZ 305) preferred.
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