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Internship Retrieval Augmented Generation Jobs (NOW HIRING)

Oraapps Inc

Agentic AI Engineer

Atlanta, GA · On-site

Develop LLM-powered applications leveraging Retrieval-Augmented Generation (RAG), tool calling, and orchestration frameworks. * Build scalable APIs, microservices, and integrations supporting ...

Pereview Software, LLC.

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 ...

ClifyX

AI Architect

Plano, TX · On-site

GPT, Claude • Prompt Engineering • RAG (Retrieval Augmented Generation) • AWS Cloud • Strong architectural and hands on GenAI expertise • Experience with enterprise automation and testing ...

Accord Technologies Inc.

GEN AI Architect

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:

Closure Technologies

AI/ML Engineer

Mclean, VA

Closure Technologies is seeking a AI/ML Engineer who will Implement and maintain Retrieval-Augmented Generation (RAG) pipelines and integrate Large Language Models (LLMs) into applications, supported ...

Winaxis

AI Engineer

Raleigh, NC · On-site

$94K - $129K/yr

... internships and academic projects are welcome). Strong programming skills in Python. Basic ... Basic understanding of Retrieval-Augmented Generation (RAG). Familiarity with vector databases such ...

Winaxis

AI Engineer

Jersey City, NJ · On-site

$101K - $139K/yr

... internships and academic projects are welcome). Strong programming skills in Python. Basic ... Basic understanding of Retrieval-Augmented Generation (RAG). Familiarity with vector databases such ...

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Internship Retrieval Augmented Generation information

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 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 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.

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Internship Retrieval Augmented Generation jobs near you
Infographic showing various Internship Retrieval Augmented Generation job openings in the United States as of September 2026, with employment types broken down into 2% Internship, 66% Full Time, 31% Part Time, and 1% Contract. Highlights an 63% Physical, 2% Hybrid, and 35% Remote job distribution.

AI / ML Engineer

Charlotte, NC • On-site

Datum Technologies Group
See more jobs at Datum Technologies Groupexternal

Full-time

Re-posted 29 days ago

Job description

Job Summary:
Datum Technologies Group is seeking an AI Engineer specializing in Conversational AI and IVR. The role involves designing, developing, and maintaining AI solutions, implementing workflows, and optimizing model performance for conversational experiences.
Responsibilities:
• Design, develop, and maintain AI solutions for IVR and conversational AI platforms.
• Implement LLM-based workflows, including prompt engineering, evaluation, and retrieval-augmented generation (RAG).
• Build and maintain knowledge retrieval pipelines to support IVR use cases such as FAQs, troubleshooting, and account-related queries.
• Evaluate and optimize model performance with a focus on accuracy, latency, and conversational quality.
• Contribute to the continuous improvement of AI-driven voice and conversational experiences.
Qualifications:
Required:
• 3+ years of experience in AI/ML development.
• Strong proficiency in Python.
• Hands-on experience with Large Language Models (LLMs), including: Prompt engineering, Model evaluation, Retrieval-Augmented Generation (RAG)
• Experience working on enterprise-scale or customer-facing systems is a plus.
Preferred:
• Experience with NLP for conversational AI applications.
• Familiarity with speech and voice data workflows, including ASR, NLU, and TTS concepts.
Company:
Datum Technologies Group provides technology solutions, managed services, government contracting, and IT staffing services. Founded in 2001, the company is headquartered in Atlanta, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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