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Rag Developer Jobs in Dallas, GA (NOW HIRING)

Onsite It Advisors LLC

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AI/ML Engineer

Atlanta, GA · On-site

$135K - $175K/yr

... RAG) applications. With strong skills in Python, SQL, and cloud platforms like Azure, you'll help ... feature engineering workflows, and large-scale data processing solutions using Python, SQL, and ...

New

Onsite It Advisors LLC

Be Seen First

AI/ML Engineer

Atlanta, GA · On-site

$135K - $175K/yr

... RAG) applications. With strong skills in Python, SQL, and cloud platforms like Azure, you'll help ... feature engineering workflows, and large-scale data processing solutions using Python, SQL, and ...

New

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Rag Developer information

What engineers make $500,000?

Senior engineers in specialized fields such as software engineering, data engineering, or engineering management can earn $500,000 or more annually, especially with extensive experience, advanced skills, and in high-demand industries like technology or finance. Compensation often includes base salary, bonuses, and stock options, particularly at large tech companies or startups with significant growth potential.

What is the difference between Rag Developer vs Textile Technician?

AspectRag DeveloperTextile Technician
CredentialsTypically requires a diploma or degree in textiles or related fieldRequires similar qualifications, often with additional certifications in textile testing
Work EnvironmentFactories, textile mills, production plantsLaboratories, quality control departments, manufacturing facilities
Industry UsageUsed in textile manufacturing to develop and process rags for reuse or recyclingInvolved in testing, quality assurance, and technical support in textile production

Both Rag Developers and Textile Technicians work within the textile industry, often in manufacturing settings. Rag Developers focus on creating and processing recycled rags, while Textile Technicians handle testing and quality control. The roles share similar educational backgrounds and work environments, but their specific responsibilities differ based on their focus within textile production.

What does a RAG engineer do?

A RAG (Red, Amber, Green) engineer develops and maintains systems that use RAG status indicators to monitor project or system health. They often work with data visualization tools, automate status reporting, and analyze performance metrics to support decision-making. Strong skills in data analysis, programming, and understanding of project management are typically required.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-paying position in artificial intelligence, such as senior machine learning engineer, AI research director, or executive roles like AI CTO. These roles often require advanced skills in programming, data analysis, and experience with AI frameworks, and they may involve leadership responsibilities or specialized expertise in cutting-edge AI technologies.

Which 3 jobs will survive AI?

For a Rag Developer, roles that require complex manual craftsmanship, creative problem-solving, and specialized knowledge are more likely to persist despite AI advancements. Jobs involving intricate textile design, custom tailoring, and quality inspection rely on human skills and judgment that AI cannot fully replicate. Developing expertise in these areas, along with staying updated on industry tools, can help ensure job security.
What job categories do people searching Rag Developer jobs in Dallas, GA look for? The top searched job categories for Rag Developer jobs in Dallas, GA are:
What cities near Dallas, GA are hiring for Rag Developer jobs? Cities near Dallas, GA with the most Rag Developer job openings:
Rag Developer jobs near you
GenAI / Agentic AI Engineer (RAG & LLM Apps

GenAI / Agentic AI Engineer (RAG & LLM Apps

ConglomerateIT LLC

Atlanta, GA • Remote

Contractor

Posted 14 days ago

Job description

Title:GenAI / Agentic AI Engineer (RAG & LLM Apps)
Location: US — Remote / Hybrid (multiple locations)
Type: Full-time or Contract (W2/C2C) 
Level: Mid–Senior (10+ Years Only)

We are hiring RAG-first GenAI engineers to build LLM-powered applications and agentic workflows for enterprise clients. This role centers on retrieval quality and reliable LLM integration as the foundation for agentic features.

What you'll do

  • Architect end-to-end RAG: chunking, embedding selection, hybrid/semantic search, re-ranking, citation and evaluation

  • Build LLM-powered microservices and APIs (FastAPI / REST)

  • Integrate and orchestrate LLMs (OpenAI, Claude, Gemini, Llama) into product and internal workflows

  • Add agentic behavior on top of RAG: tool-calling, multi-step task execution, guardrails, hallucination handling

  • Stand up and tune vector-store infrastructure; deploy and monitor in production

Must have

  • Strong Python

  • End-to-end RAG experience

  • Vector databases (Pinecone, Weaviate, pgvector, FAISS, or similar)

  • LLM API integration (OpenAI / Anthropic / Gemini / Llama)

  • LangChain and/or LlamaIndex

  • FastAPI / REST and one cloud (AWS, Azure, or GCP)

Nice to have

  • LangGraph, MCP, DSPy

  • Knowledge graphs / Neo4j, evals/LangSmith, MLOps

Founded in 2014, ConglomerateIT is a global leader in delivering innovative IT solutions and services. Headquartered in the USA with a presence in the UK, Canada, and India, we specialize in offering industry-leading expertise and cutting-edge products that help our clients maximize their technological investments. Our focus on best-in-class solutions, a highly knowledgeable team, and proactive talent mapping ensure we remain at the forefront of the IT industry.

ConglomerateIT is driven by our Center for Excellence and Innovation, an initiative dedicated to keeping us ahead in a rapidly evolving technology landscape. We understand that building strong relationships is key to our success, and this commitment has enabled us to partner with Fortune 500 companies and leading system integrators worldwide. Our ability to provide local talent on a global scale ensures that we can meet the contingent project requirements of our clients efficiently and effectively.