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Internship Retrieval Augmented Generation Jobs (NOW HIRING)

Develop Retrieval-Augmented Generation (RAG) solutions and AI workflows. Work with Large Language Models (LLMs) such as OpenAI, Azure OpenAI, or similar platforms. Collaborate with product managers ...

AI/ML Engineer

Plano, TX · On-site

$109K - $131K/yr

Fine-tune foundation models and implement Retrieval-Augmented Generation (RAG) architectures. * Develop REST APIs and microservices using FastAPI, Flask, or similar frameworks to expose AI models.

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

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

The role focuses on Retrieval Augmented Generation (RAG), semantic search, vector databases, metadata engineering, and enterprise knowledge orchestration to deliver secure, accurate, and context ...

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

Senior AI Technologist

Albuquerque, NM · On-site +1

$50.50 - $65/hr

Working closely with business units, engineers, and functional teams, you will leverage applied AI technologies including large language models (LLMs), retrieval-augmented generation (RAG), AI agents ...

Develop Retrieval-Augmented Generation (RAG) pipelines using vector databases. * Create AI agents and workflow automation solutions. * Fine-tune, evaluate, and optimize AI models for performance and ...

Senior AI Technologist

Raleigh, NC · On-site +1

$48.75 - $63/hr

Working closely with business units, engineers, and functional teams, you will leverage applied AI technologies including large language models (LLMs), retrieval-augmented generation (RAG), AI agents ...

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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.

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Infographic showing various Internship Retrieval Augmented Generation job openings in the United States as of July 2026, with employment types broken down into 91% Full Time, 6% Part Time, and 3% Contract. Highlights an 76% Physical, 4% Hybrid, and 20% Remote job distribution.

Senior Applied AI Engineer - Software Engineering with Security Clearance

Neural Solutions

Columbia, MD • On-site

$204K - $247K/yr

Other

Posted 2 days ago

New


Job description


Join a fast-moving Tactical AI team developing production-quality AI applications that accelerate mission workflows through large language models (LLMs), retrieval-augmented generation (RAG), and modern software engineering practices. As part of this dynamic team, you will work directly with mission customers to design and develop AI-powered solutions that solve complex operational challenges. Responsibilities: * Design, develop, and maintain production AI-enabled software applications using Python and modern software engineering practices.
* Architect and implement LLM-powered workflows, retrieval-augmented generation (RAG) pipelines, and AI agent capabilities that solve mission problems. Required Skills: * Production software development experience using Python.
* Experience designing and developing distributed or backend software systems.
* Experience building AI-enabled applications using LLMs, retrieval-augmented generation (RAG), AI agents, or similar technologies. Nice to Have: * Experience with Model Context Protocol (MCP), PydanticAI, LangChain, LlamaIndex, or similar AI frameworks.
* Experience deploying applications using Docker, Kubernetes, or containerized environments. Experience Required: 12 years with Bachelor's degree in a technical field, or 16 years without degree Location: Columbia, MD Clearance: TS/SCI with Polygraph required Salary Range: $204,000 - $247,000