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Overnight 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 ...

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 ...

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 ...

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 ...

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Overnight Retrieval Augmented Generation information

What is the difference between Overnight Retrieval Augmented Generation vs Data Scientist?

AspectOvernight Retrieval Augmented GenerationData Scientist
CredentialsTypically requires knowledge of AI, NLP, and data retrieval techniquesRequires degrees in data science, statistics, or related fields
Work EnvironmentOften in AI research labs, tech companies, or startups focusing on NLP modelsIn corporate, research, or consulting settings analyzing data and building models
Industry UsagePrimarily in AI, machine learning, and NLP industriesAcross finance, healthcare, tech, and other sectors

Overnight Retrieval Augmented Generation focuses on developing AI models that combine retrieval techniques with generative AI, often working overnight to update or improve models. Data Scientists analyze data, build predictive models, and interpret results across various industries. While both roles involve data and AI, Retrieval Augmented Generation specialists focus on model training and NLP innovations, whereas Data Scientists handle broader data analysis and modeling tasks.

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Overnight Retrieval Augmented Generation jobs near you
Infographic showing various Overnight Retrieval Augmented Generation job openings in Georgia as of August 2026, with employment types broken down into 72% Full Time, 26% Part Time, and 2% Contract. Highlights an 62% Physical, 3% Hybrid, and 35% Remote job distribution.

Qdrant Developer

Cliff Services Inc

Alpharetta, GA • On-site

Other

Posted 16 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.

Apply