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Internship Retrieval Augmented Generation Jobs in Georgia

Cliff Services Inc

Qdrant Developer

Alpharetta, GA · On-site

Knowledge of RAG (Retrieval-Augmented Generation) architectures. * Experience integrating Qdrant with LLM frameworks such as LangChain or LlamaIndex. * Familiarity with REST APIs and microservices.

eTeam

Artificial Intelligence Engineer

Alpharetta, GA · On-site

$108K - $130K/yr

... Retrieval-Augmented Generation (RAG) and reasoning pipelines to ensure grounded, reliable, and adaptive agent behavior. • Collaborate closely with GenAI engineers, application teams, MLOps, product ...

Insight Global

AI Engineer

Atlanta, GA · On-site +1

... retrieval-augmented generation (RAG) and reranking; agent orchestration with LangGraph or comparable; or LLM fine-tuning. • Proficient in Python and comfortable working with async code, data ...

JR Software Solutions, Inc.

AI/ML Engineer

Atlanta, GA · On-site +1

Build and enhance Generative AI, LLM, and Retrieval-Augmented Generation (RAG) applications, including chatbot and conversational AI capabilities. * Develop and optimize data pipelines, feature ...

Virtual Networx

AI/ML Engineer

Atlanta, GA · On-site

Retrieval-Augmented Generation (RAG) * Vector Databases (Pinecone, FAISS, ChromaDB, Milvus) * LangChain or LlamaIndex * SQL and NoSQL databases * REST APIs and FastAPI/Flask * Git and CI/CD * AWS ...

CYNET SYSTEMS

AI Engineer

Atlanta, GA · On-site

$50 - $55/hr

Develop and implement Retrieval Augmented Generation (RAG) solutions for knowledge retrieval and contextual AI responses. Design AI orchestration workflows using frameworks such as LangChain ...

CYNET SYSTEMS

AI Engineer

Atlanta, GA · On-site

$50 - $55/hr

Develop and implement Retrieval Augmented Generation (RAG) solutions for knowledge retrieval and contextual AI responses. * Design AI orchestration workflows using frameworks such as LangChain ...

Spruce Infotech

Agentic Gen AI Engineer

Alpharetta, GA · On-site

... Retrieval-Augmented Generation (RAG) and reasoning pipelines to ensure grounded, reliable, and adaptive agent behavior. • Collaborate closely with GenAI engineers, application teams, MLOps, product ...

Fisec Global

Gen AI Engineer

Atlanta, GA · On-site

... Retrieval Augmented Generation (RAG), Fine tuning LLMs, Prompt tuning, Graph RAGs, Knowledge graphs ... Experience mentoring junior colleagues and interns.

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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 Georgia? The most popular types of Retrieval Augmented Generation jobs in Georgia are:
What are popular job titles related to Internship Retrieval Augmented Generation jobs in Georgia? For Internship Retrieval Augmented Generation jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Internship Retrieval Augmented Generation jobs in Georgia look for? The top searched job categories for Internship Retrieval Augmented Generation jobs in Georgia are:
What cities in Georgia are hiring for Internship Retrieval Augmented Generation jobs? Cities in Georgia with the most Internship Retrieval Augmented Generation job openings:
Internship Retrieval Augmented Generation jobs near you
Infographic showing various Internship Retrieval Augmented Generation job openings in Georgia as of August 2026, with employment types broken down into 64% Full Time, 33% Part Time, and 3% Contract. Highlights an 62% Physical, 3% Hybrid, and 35% Remote job distribution.

Qdrant Developer

Cliff Services Inc

Alpharetta, GA • On-site

Other

Posted 19 days ago

Job description

Position: Qdrant Developer
Duration: 12+ Months

Interview Mode: Virtual

Job Description

We are seeking a skilled Qdrant Developer with hands-on experience in vector databases and AI-powered search applications. The ideal candidate should have experience designing, implementing, and optimizing vector search solutions using Qdrant for Retrieval-Augmented Generation (RAG) and semantic search use cases.

Required Skills

  • 3+ years of software development experience with Python.
  • Hands-on experience with Qdrant Vector Database.
  • Strong understanding of vector embeddings and semantic search.
  • Experience with embedding models such as OpenAI, Sentence Transformers, or Hugging Face.
  • Knowledge of RAG (Retrieval-Augmented Generation) architectures.
  • Experience integrating Qdrant with LLM frameworks such as LangChain or LlamaIndex.
  • Familiarity with REST APIs and microservices.
  • Experience with Docker and Kubernetes is a plus.
  • Knowledge of cloud platforms (AWS, Azure, or Google Cloud Platform).
  • Strong problem-solving and debugging skills.

Responsibilities

  • Design, develop, and maintain vector search solutions using Qdrant.
  • Build and optimize semantic search and RAG pipelines.
  • Create and manage vector collections, indexing, and embeddings.
  • Integrate Qdrant with AI/ML applications and LLM frameworks.
  • Optimize search performance, scalability, and data retrieval.
  • Collaborate with AI engineers, data scientists, and application developers.
  • Monitor, troubleshoot, and improve vector database performance.

Preferred Qualifications

  • Experience with Generative AI and Large Language Models (LLMs).
  • Knowledge of FastAPI or Flask.
  • Experience with Git, CI/CD, and Agile development methodologies.
  • Bachelor's degree in Computer Science, Engineering, or a related field.

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