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Retrieval Augmented Generation Rag Jobs in Atlanta, GA

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 ...

Marici Solutions

Palantir GEN AI Engineer

Atlanta, GA · On-site

Build retrieval-augmented generation (RAG) and ontology-augmented generation (OAG) workflows grounded in Foundry data. Develop copilots, decision-support agents and autonomous workflows using AIP ...

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 ...

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 ...

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 ...

Purple Drive

AI/ML Engineer

Atlanta, GA · On-site

$110K - $132K/yr

Experienced AI/ML Engineer with expertise in Machine Learning, Deep Learning, NLP,and Generative AI. strong expertise in LLMs, Retrieval-Augmented Generation (RAG),Agentic AI, and MLOps to develop ...

Monitise

Director, AI - Cyber Security I

Alpharetta, GA · On-site

Architect and implement multi-agent and agentic AI frameworks that support enterprise cybersecurity use cases, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), embeddings ...

FAVARH

AI Principal Engineer

Atlanta, GA · On-site +1

Lead the design, development, and deployment of complex AI solutions, including LLM-based applications, retrieval-augmented generation (RAG) pipelines, and model-driven services. * Own technical ...

Vibotek LLC

Agentic AI Developer

Atlanta, GA · On-site

... Retrieval-Augmented Generation (RAG) and knowledge-grounded AI solutions • Integrate AI agents with enterprise systems via REST APIs, databases, and cloud services • Build agent memory, tool ...

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Retrieval Augmented Generation Rag information

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How much do retrieval augmented generation rag jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for retrieval augmented generation rag in Atlanta, GA is $19.47, according to ZipRecruiter salary data. Most workers in this role earn between $16.63 and $20.34 per hour, depending on experience, location, and employer.

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Retrieval Augmented Generation Rag jobs near you
Infographic showing various Retrieval Augmented Generation Rag job openings in Atlanta, GA 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, with an average salary of $40,504 per year, or $19.5 per hour.

Agentic AI Engineer

Oraapps Inc

Atlanta, GA • On-site

Other

Posted 23 days ago

Key responsibilities

  • Design, develop, and deploy enterprise-grade AI applications using modern software engineering practices.

  • Build and enhance agentic AI solutions, AI copilots, and workflow automation.

  • Collaborate with data scientists to productionize machine learning and AI solutions.

Job description

What You''ll Do

  • Design, develop, and deploy enterprise-grade AI applications using modern software engineering best practices.
  • Build and enhance agentic AI solutions, AI copilots, and intelligent workflow automation.
  • Develop LLM-powered applications leveraging Retrieval-Augmented Generation (RAG), tool calling, and orchestration frameworks.
  • Build scalable APIs, microservices, and integrations supporting enterprise AI platforms.
  • Collaborate with data scientists to productionize machine learning and AI solutions.
  • Implement testing, monitoring, observability, and governance practices for AI applications.
  • Ensure AI solutions meet security, compliance, and responsible AI standards.
  • Contribute to architecture decisions for enterprise AI platforms and reusable application frameworks.
  • Work within Azure and Microsoft''s AI ecosystem while supporting multi-cloud best practices where appropriate.
  • Participate in code reviews and promote engineering excellence across the team.

Current AI Initiatives

  • This role will contribute to several strategic AI initiatives, including:
  • Payer Intelligence Platform
  • Monitor payer policy changes using AI.
  • Assess operational impact of policy updates.
  • Support managed care teams in prioritizing actions and dispute resolution.
    • Clinical Chart Review: Build agentic AI solutions using EHR and clinical documentation.
  • Support patient cohort identification.
  • Generate clinical insights for quality improvement initiatives.
  • Population Market Intelligence: Analyze internal and external datasets.
  • Generate recommendations for service line growth.
  • Identify emerging healthcare market opportunities.

Required Qualifications

  • MUST HAVE A Bachelor''s degree in Computer Science, Engineering, Data Science, or a related technical field. Master''s degree preferred. Equivalent professional experience may be considered in lieu of an advanced degree.
  • Approximately 3+ years of experience in AI engineering, machine learning engineering, data engineering, software engineering, or a related technical discipline.
  • At least 2 years of experience designing, building, and supporting production-grade enterprise applications.
  • Hands-on experience developing applications using Large Language Models (LLMs).
  • Experience implementing Retrieval-Augmented Generation (RAG) architectures.
  • Experience building agentic AI applications, AI assistants, or workflow automation solutions.
  • Strong Python programming skills.
  • Experience building and consuming RESTful APIs.
  • Knowledge of software engineering best practices, including testing, version control, CI/CD, and maintainable application design.
  • Experience designing scalable enterprise application architectures.

Preferred Qualifications

  • Experience within healthcare, provider organizations, payer organizations, or biomedical environments.
  • Experience with Microsoft Azure and Azure AI services.
  • Familiarity with GitHub Copilot and the Microsoft AI ecosystem.
  • Experience with AI governance, responsible AI practices, observability, guardrails, and model monitoring.
  • Background in MLOps and production AI deployment.
  • Technical Environment
  • Python
  • Azure (preferred)
  • GitHub Copilot
  • Microsoft AI ecosystem
  • REST APIs
  • Microservices
  • Enterprise AI architecture
  • Tool-calling frameworks
  • Retrieval-Augmented Generation (RAG)

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