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Rag Developer Jobs in Arizona (NOW HIRING)

Java AI Developer

Phoenix, AZ · On-site

$50.25 - $65/hr

Candidates should have practical experience building GenAI applications using LLMs, Retrieval-Augmented Generation (RAG), vector databases, prompt engineering, AI agents, and enterprise AI governance.

Lead Gen AI Engineer with Python

Phoenix, AZ · On-site

$139K - $170K/yr

Lead Gen AI Engineer with Python We are looking for a Lead Gen AI Engineer with strong expertise in Python, Generative AI, Retrieval-Augmented Generation (RAG), and Agentic AI to lead the design and ...

Senior Java Backend Developer - GenAI

Phoenix, AZ · On-site

$119K - $155K/yr

Candidates should have practical experience building GenAI applications using LLMs, Retrieval-Augmented Generation (RAG), vector databases, prompt engineering, AI agents, and enterprise AI governance.

AI Engineering Leader

Tempe, AZ · On-site

$98K - $129K/yr

This role i not a pure management role - the ideal candidate will actively design, build, and scale AI systems (RAG, agents, evaluation frameworks) while leading engineering initiatives and ...

Lead Gen AI Engineer

Phoenix, AZ · On-site

$101K - $134K/yr

We are looking for a Lead Gen AI Engineer with strong expertise in Python, Generative AI, Retrieval-Augmented Generation (RAG), and Agentic AI to lead the design and development of enterprise AI ...

Gen AI Engineer with Python We are looking for a Gen AI Engineer with strong expertise in Python, Generative AI, Retrieval-Augmented Generation (RAG), and Agentic AI to lead the design and ...

Job Title - Gen AI Engineer Location - Phoenix, AZ Duration: 12+ Months Interview Mode - In-Person Interview Tech Stack - AI / Agentic AI, LLM, RAG, FastAPI, GCP, Flask, Python, SQL, Docker ...

Build and enhance AI/ML and GenAI-powered solutions using Python, LLMs, RAG, prompt engineering, and agentic AI frameworks * Develop models for NLP, classification, clustering, anomaly detection, and ...

Junior AI Engineer Location: Phoenix, AZ Job Type: Only W2 · Develop and deploy AI/ML models for ... LLMs. · Develop RAG (Retrieval-Augmented Generation) pipelines using embeddings and vector ...

Data Engineer

Phoenix, AZ · On-site

$113K - $136K/yr

Familiarity with AI/ML and Generative AI - vector databases, embeddings, semantic search, LLMs, and RAG * Experience with Infrastructure as Code and DevOps/CI/CD practices * Knowledge of database ...

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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 job categories do people searching Rag Developer jobs in Arizona look for?

The top searched job categories for Rag Developer jobs in Arizona are:

What cities in Arizona are hiring for Rag Developer jobs?

Cities in Arizona with the most Rag Developer job openings:

Infographic showing various Rag Developer job openings in Arizona as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Java AI Developer

Omega Hires

Phoenix, AZ • On-site

$50.25 - $65/hr

Other

Posted 18 days ago


Job description

Job Description: Position Summary

  • We are seeking a Senior Java Backend Developer with 8+ years of experience building enterprise-grade backend applications and mandatory hands-on experience with Generative AI (GenAI) technologies. The ideal candidate must possess strong expertise in Java, Spring Boot, Microservices, Distributed Systems, Kafka, Cloud Technologies, and LLM-powered application development.
  • This role focuses on designing and delivering secure, scalable, AI-enabled backend services for Digital Banking platforms. Candidates should have practical experience building GenAI applications using LLMs, Retrieval-Augmented Generation (RAG), vector databases, prompt engineering, AI agents, and enterprise AI governance.
  • Required Experience
  • 8+ years of hands-on Java Backend Development experience.
  • 3+ years of hands-on Generative AI development experience (Mandatory).
  • Strong experience building enterprise applications using Java, Spring Boot, and Microservices.
  • Experience working in Banking, Financial Services, FinTech, or highly regulated environments is highly preferred.
  • Key Responsibilities
  • Design and develop scalable backend applications using Java, Spring Boot, and Microservices.
  • Build enterprise-grade RESTful APIs and event-driven applications using Kafka.
  • Design distributed systems with high availability, resiliency, fault tolerance, and scalability.
  • Develop AI-powered backend services using Large Language Models (LLMs).
  • Build and optimize Retrieval-Augmented Generation (RAG) pipelines for enterprise knowledge retrieval.
  • Implement AI Agents, tool/function calling, prompt engineering, structured outputs, and workflow orchestration.
  • Integrate vector databases and semantic search capabilities into enterprise applications.
  • Develop secure APIs for AI services while ensuring governance, compliance, and data privacy.
  • Collaborate with Product Managers, Architects, and Data Science teams to deliver AI-driven business capabilities.
  • Mentor engineers and participate in architecture discussions, code reviews, and technical design sessions.
  • Build CI/CD pipelines and support production deployments.