ZipRecruiter

Log In

1

Temporary Retrieval Augmented Generation Jobs (NOW HIRING)

TekShapers

Gen AI Architect

Raritan, NJ · On-site

Design and implement Retrieval-Augmented Generation (RAG) architectures using vector databases and enterprise data sources. * Collaborate with business stakeholders, product teams, and engineering ...

CYNET SYSTEMS

Senior AI Engineer - Privacy

Bellevue, WA · On-site

$70 - $75/hr

This role involves applying large language models, retrieval-augmented generation, multi-agent orchestration, and foundation model capabilities to automate and enhance privacy operations. Requirement ...

Tekshapers Inc

Generative AI/ML Engineer

New York, NY · On-site

The ideal candidate will have a strong background in investment banking, hands-on experience with Microsoft Azure OpenAI, and expertise in Retrieval-Augmented Generation (RAG). Key Responsibilities:

Compunnel

Senior Data Scientist GenAI / RAG

Houston, TX · On-site

Build, deploy, and optimize Retrieval-Augmented Generation (RAG) systems and AI-powered chat interfaces. * Develop enterprise Generative AI solutions using Large Language Models (LLMs) and related ...

Pereview Software

AI Engineer

Dallas, TX · On-site

Develop and maintain Retrieval-Augmented Generation (RAG) architectures using vector databases and semantic search technologies * Create, test, and refine prompts, structured outputs, and evaluation ...

Pereview Software

AI Engineer

Dallas, TX · On-site

Develop and maintain Retrieval-Augmented Generation (RAG) architectures using vector databases and semantic search technologies * Create, test, and refine prompts, structured outputs, and evaluation ...

Redolent, Inc.

Sr, ML Architect

Washington, DC · On-site

Integrate with large language models (LLMs) and generative AI (GenAI) using prompt engineering, fine-tuning, and retrieval-augmented generation (RAG) techniques. * Implement MCP client and server ...

CGI

GenAI Context Engineer

Pittsburgh, PA · On-site

Design and implement enterprise Retrieval Augmented Generation (RAG) architectures for GenAI platforms and applications. . Build and optimize semantic retrieval pipelines, vector search ...

CGI Inc.

GenAI Context Engineer

Pittsburgh, PA · On-site

Design and implement enterprise Retrieval Augmented Generation (RAG) architectures for GenAI platforms and applications. . Build and optimize semantic retrieval pipelines, vector search ...

Pereview Software

AI Engineer

Dallas, TX · On-site

Develop and maintain Retrieval-Augmented Generation (RAG) architectures using vector databases and semantic search technologies * Create, test, and refine prompts, structured outputs, and evaluation ...

next page

Showing results 1-20

All JobsRetrieval Augmented Generation JobsTemporary Retrieval Augmented Generation Jobs

Temporary Retrieval Augmented Generation information

See salary details

$13

$20

$29

How much do temporary retrieval augmented generation jobs pay per hour?

As of Jul 10, 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?

AspectTemporary Retrieval Augmented GenerationData Scientist
Required CredentialsTypically requires knowledge of AI, NLP, and some programming skillsRequires degrees in data science, statistics, or related fields, often with certifications in data analysis
Work EnvironmentOften project-based, working with AI models and large datasets in tech or research firmsUsually in corporate, research, or tech companies analyzing data to inform decisions
Industry UsageUsed in AI development, natural language processing, and machine learning projectsApplied 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
What cities are hiring for Temporary Retrieval Augmented Generation jobs? Cities with the most Temporary Retrieval Augmented Generation job openings:
What are the most commonly searched types of Retrieval Augmented Generation jobs? 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:
Temporary Retrieval Augmented Generation jobs near you
Infographic showing various Temporary Retrieval Augmented Generation job openings in the United States as of July 2026, with employment types broken down into 90% Full Time, 8% Part Time, and 2% Contract. Highlights an 77% Physical, 3% Hybrid, and 20% Remote job distribution, with an average salary of $43,381 per year, or $20.9 per hour.

AI-Native Developer / Engineer (Hybrid)

Siritech Solutions Corp

Whippany, NJ

Full-time

Re-posted 7 days ago

Job description

Mode of Work: Hybrid
Job Description:Seeking an experienced AI-Native Developer / Engineer to build AI-first applications with Artificial Intelligence embedded into core architecture, workflows, and delivery lifecycles from inception. The ideal candidate should possess strong expertise in Large Language Models (LLMs), agentic workflows, Retrieval-Augmented Generation (RAG), AI-powered software development, API integrations, and cloud-native deployments. This role requires hands-on experience building autonomous or semi-autonomous AI agents, orchestrating planning loops, integrating LLMs into applications, implementing memory modules, developing production-ready AI solutions, and accelerating delivery using AI-assisted development tools and modern software engineering practices.

Key Responsibilities:

  • Design, develop, test, and deploy AI-native applications with embedded Artificial Intelligence capabilities
  • Build autonomous or semi-autonomous agentic systems and orchestrate planning workflows
  • Develop and implement Large Language Model (LLM)-based solutions and agentic workflows
  • Build Retrieval-Augmented Generation (RAG) systems using semantic search and vector databases
  • Integrate OpenAI, Anthropic, and other LLM APIs using function calling, structured outputs, and workflow orchestration
  • Utilize AI coding tools such as Cursor, GitHub Copilot, and Claude Code for rapid prototyping and development acceleration
  • Develop scalable backend and frontend components using Python, TypeScript/JavaScript, React, Next.js, and Node.js
  • Support production deployment of AI applications using AWS, GCP, Azure, Vercel, Docker, and Kubernetes
  • Implement testing, debugging, API design, clean code practices, and version control standards
  • Support AI governance, security, human-in-the-loop workflows, and responsible AI implementation practices


Additional Responsibilities:

  • Collaborate with engineering, product, and business teams to accelerate AI adoption and delivery
  • Support Proof of Concept (PoC) to production deployment lifecycle activities
  • Optimize AI workflows, agent orchestration, and application performance
  • Participate in AI experimentation, innovation, and continuous learning initiatives
  • Maintain enterprise software engineering and AI development best practices


Required Skills:

  • Strong proficiency in Python and TypeScript/JavaScript (React, Next.js, Node.js)
  • Strong experience with Large Language Models (LLMs), agentic workflows, and AI-native application development
  • Experience with LangChain, LangGraph, LlamaIndex, or Semantic Kernel frameworks
  • Experience building Retrieval-Augmented Generation (RAG) systems and semantic search workflows
  • Familiarity with vector databases such as Pinecone, Chroma, Milvus, or Vertex AI Vector Search
  • Hands-on experience using AI development tools such as Cursor, Claude Code, and GitHub Copilot
  • Strong software engineering fundamentals including Git, testing, debugging, API design, and clean coding practices
  • Experience with Docker, Kubernetes, cloud deployment platforms, and MLOps tools preferred
  • Understanding of AI governance, security, and human-in-the-loop mechanisms preferred
  • Experience building custom GPTs, Claude Projects, or multi-agent orchestration preferred


Qualifications:

  • Strong experience building AI-native or LLM-powered applications preferred
  • Experience supporting agentic workflows and AI automation initiatives preferred
  • Strong adaptability and ability to rapidly adopt emerging AI technologies preferred
  • Strong product mindset and ability to quickly deliver scalable AI solutions preferred