The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
AI Programmer Analyst
Little Falls, NJ · On-site
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
AI Programmer Analyst
Little Falls, NJ · On-site
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
AI Programmer Analyst
Harrison, NJ · On-site
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
AI Programmer Analyst
Harrison, NJ · On-site
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...
Temporary Retrieval Augmented Generation information
See salary details
$13.70 - $15.17
1% of jobs
$15.17 - $16.63
21% of jobs
$16.85 is the 25th percentile. Wages below this are outliers.
$16.63 - $18.09
18% of jobs
The median wage is $19.41 / hr.
$18.09 - $19.56
11% of jobs
$19.56 - $21.02
10% of jobs
$21.02 - $22.49
11% of jobs
$23.22 is the 75th percentile. Wages above this are outliers.
$22.49 - $23.95
7% of jobs
$23.95 - $25.42
6% of jobs
$25.42 - $26.88
6% of jobs
$26.88 - $28.34
5% of jobs
$28.34 - $29.81
3% of jobs
$13
$20
$29
How much do temporary retrieval augmented generation jobs pay per hour?
As of Aug 20, 2026, the average hourly pay for temporary retrieval augmented generation in the United States is $20.86, according to ZipRecruiter salary data. Most workers in this role earn between $16.35 and $24.28 per hour, depending on experience, location, and employer.
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.
More about Temporary Retrieval Augmented Generation jobs
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Cities with the most Temporary Retrieval Augmented Generation job openings:
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The most popular types of Retrieval Augmented Generation jobs are:
What states have the most Temporary Retrieval Augmented Generation jobs?
States with the most job openings for Temporary Retrieval Augmented Generation jobs include:
What job categories do people searching Temporary Retrieval Augmented Generation jobs look for?
The top searched job categories for Temporary Retrieval Augmented Generation jobs are:
Full-time
Posted 7 days ago
Job description
Job Summary
We are seeking an experienced AI Programmer Analyst to design, develop, and implement enterprise AI solutions that solve complex business challenges and improve operational efficiency. The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI platforms. This role involves collaborating with business and technology teams to deliver scalable, secure, and responsible AI solutions from concept through production deployment.
Roles and Responsibilities- Partner with business and technology stakeholders to identify, evaluate, and implement AI-driven solutions.
- Design, prototype, develop, test, deploy, and maintain enterprise AI applications and intelligent automation solutions.
- Evaluate and select appropriate AI models, frameworks, and architectures based on business and technical requirements.
- Develop and optimize prompts, AI agents, workflows, orchestration pipelines, and retrieval strategies to improve solution accuracy and effectiveness.
- Integrate AI solutions with enterprise applications, APIs, databases, and business processes.
- Build scalable AI solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agent-based architectures.
- Design AI-powered monitoring pipelines that analyze application, server, and database logs to predict system anomalies, recommend real-time resolutions, and automate root-cause analysis.
- Monitor AI model performance, reliability, accuracy, and adoption while continuously improving deployed solutions.
- Ensure AI solutions comply with security, governance, privacy, and Responsible AI standards.
- Create technical documentation, architecture diagrams, implementation guides, and operational runbooks.
- Participate in CI/CD processes, source control, testing, and DevOps practices for AI application delivery.
- Research and recommend emerging AI technologies, frameworks, and best practices.
- 2–10 years of experience in software development, AI application development, or machine learning engineering.
- Strong experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and AI orchestration frameworks.
- Hands-on experience with enterprise AI platforms such as Azure AI, Microsoft Copilot Studio, Gemini Enterprise, or similar AI services.
- Strong Python programming skills with AI/ML libraries and frameworks.
- Experience integrating AI solutions with enterprise applications, REST APIs, databases, and cloud platforms.
- Strong SQL and data analysis skills.
- Experience with cloud-based AI services and enterprise AI platforms.
- Solid understanding of AI/ML concepts, model evaluation techniques, model limitations, and Responsible AI practices.
- Experience with Git, version control, DevOps, and CI/CD pipelines.
- Strong analytical, problem-solving, communication, and documentation skills.
- Experience implementing AIOps solutions for predictive log analysis, automated incident remediation, and root-cause analysis.
- Experience with monitoring and observability platforms.
- Familiarity with MLOps practices, model deployment, monitoring, and lifecycle management.
- Experience developing scalable AI applications in cloud environments.
- Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or a related field (or equivalent experience).