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Internship Retrieval Augmented Generation Jobs in Arizona

Senior Java Backend Developer - GenAI

Phoenix, AZ ยท 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.

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Data Analyst

Phoenix, AZ ยท On-site

$90K - $130K/yr

... Retrieval-Augmented Generation (RAG), and Agentic AI technologies. Working within a highly regulated financial environment, you will contribute to building scalable data solutions and support AI ...

Engineer II Premium

Phoenix, AZ

$82K - $110K/yr

... Skills: - Retrieval-Augmented Generation (RAG) - Prompt engineering and optimization - Data Modeling - Synthetic Data Generation - Exploratory Data Analysis - Data cleaning and preprocessing ...

Java GENAI Engineer

Phoenix, AZ ยท On-site

$100K - $130K/yr

LLM APIs (OpenAI / Gemini / Claude) โ€ข Prompt engineering Understanding of: โ€ข RAG (Retrieval-Augmented Generation) โ€ข Embeddings & vector databases Roles & Responsibilities โ€ข Experience with ...

Design and implement production AI platform capabilities, including agents, retrieval-augmented generation, tool calling, workflow orchestration, evaluation, and human review. * Build an AI-native ...

Retrieval-Augmented Generation (RAG) architectures * AI agents and orchestration frameworks * Develops intelligent copilots and assistants using Copilot Studio, integrating enterprise data and ...

Build and maintain content vectorization and retrieval-augmented generation (RAG) pipelines that give AI agents access to relevant financial context, including prior work product, regulatory guidance ...

AI Engineer III

Phoenix, AZ ยท On-site

$103K - $174K/yr

Help implement and maintain retrieval-augmented generation (RAG) pipelines over financial data ... Internship or early-career experience in fintech or other regulated environments. * Contributions ...

AI Engineer III - Agentic AI

Phoenix, AZ ยท On-site

$103K - $174K/yr

Help implement and maintain retrieval-augmented generation (RAG) pipelines over financial data ... Internship or early-career experience in fintech or other regulated environments. * Contributions ...

Architect and deliver integrated AI solutions, including agentic workflows, retrieval-augmented generation pipelines, and enterprise platform integrations * Define and enforce governance, security ...

Integrate with large language models (LLMs) using prompt engineering, fine-tuning, and retrieval-augmented generation (RAG) techniques. * Implement MCP client and server within the Grafana ecosystem ...

LLMs * retrieval-augmented generation (RAG) * automation and code generation * Strong software skills (Java and Python), including: * test program development * scripting or tool development * Proven ...

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Internship Retrieval Augmented Generation information

What are the key skills and qualifications needed to thrive as an intern working with Retrieval Augmented Generation (RAG), and why are they important?

To thrive as an intern in Retrieval Augmented Generation, you need a foundational understanding of natural language processing, machine learning concepts, and strong programming skills, often supported by coursework or research in computer science or data science. Familiarity with tools like Python, PyTorch or TensorFlow, and experience with libraries such as Hugging Face Transformers and vector databases are typically required. Strong analytical thinking, curiosity, and effective communication make candidates stand out in collaborative, research-intensive environments. These abilities are critical for developing, evaluating, and improving RAG systems that combine information retrieval with generative models.

What is an Internship in Retrieval Augmented Generation (RAG)?

An Internship in Retrieval Augmented Generation (RAG) is a temporary position, typically for students or early-career professionals, focused on developing or researching AI systems that combine information retrieval with generative models. Interns in this field may work on enhancing how AI models find and use external data sources to generate accurate, context-aware responses. This role often involves tasks such as data preprocessing, implementing retrieval algorithms, fine-tuning language models, and evaluating system performance. It offers valuable hands-on experience with cutting-edge AI technologies and frameworks.

What types of projects or tasks can I expect to work on during an Internship in Retrieval Augmented Generation (RAG)?

As an intern in Retrieval Augmented Generation, you can expect to work on projects that involve integrating information retrieval systems with generative AI models. Typical tasks may include curating and preprocessing data sets, developing or fine-tuning retrieval algorithms, evaluating the performance of RAG pipelines, and collaborating with engineers and researchers to improve end-to-end system accuracy. You may also assist in conducting experiments, analyzing results, and documenting findings, all within a collaborative team environment that values innovation and knowledge sharing.

What is the difference between Internship Retrieval Augmented Generation vs Internship Data Analyst?

AspectInternship Retrieval Augmented GenerationInternship Data Analyst
Required SkillsKnowledge of AI, NLP, retrieval systems, programmingData analysis, statistical skills, Excel, SQL
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, marketing departments
Employer UsageDevelop AI models, improve retrieval systemsAnalyze data trends, generate reports

Internship Retrieval Augmented Generation focuses on developing AI models that combine retrieval systems with language generation, requiring skills in AI and programming. In contrast, an Internship Data Analyst concentrates on analyzing data sets to inform business decisions, emphasizing statistical and analytical skills. Both roles are common in tech and business sectors but serve different functions within organizations.

What are the most commonly searched types of Retrieval Augmented Generation jobs in Arizona? The most popular types of Retrieval Augmented Generation jobs in Arizona are:
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What cities in Arizona are hiring for Internship Retrieval Augmented Generation jobs? Cities in Arizona with the most Internship Retrieval Augmented Generation job openings:
Senior Java Backend Developer - GenAI

Senior Java Backend Developer - GenAI

OmegaHires

Phoenix, AZ โ€ข On-site

$119K - $155K/yr

Contractor

Posted yesterday


Job description

Senior Java Backend Developer - GenAI
Job Description: Position SummaryWe 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 Experience8+ 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 ResponsibilitiesDesign 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.