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Rag Developer Jobs in Dallas, TX (NOW HIRING)

We are seeking an AI Engineer to design and deploy production-grade AI solutions across LLM applications, RAG pipelines, retrieval systems, and scalable ML services. This role blends model ...

Lead Data Engineer

Lake Dallas, TX · On-site

$111K - $133K/yr

RAG implementation, semantic search, AI agents - LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel * Azure Data Factory, Talend, or Python-based ETL frameworks * DevOps, CI/CD, Infrastructure-as ...

RAG pipelines: use Hugging Face, LangChain, and Open AI API to architect RAG pipelines and ... AI Engineer with 6-9 years of experience. Hands-on experience in shop floor operations, production ...

RAG Pipeline Security * Harden RAG pipelines against retrieval manipulation attacks, indirect ... Engineer andmaintainnetwork security controls including segmentation andmicrosegmentation, secure ...

RAG Pipeline Security * Harden RAG pipelines against retrieval manipulation attacks, indirect ... Engineer andmaintainnetwork security controls including segmentation andmicrosegmentation, secure ...

RAG Pipeline Security * Harden RAG pipelines against retrieval manipulation attacks, indirect ... Engineer andmaintainnetwork security controls including segmentation andmicrosegmentation, secure ...

AI/ML Software Engineer

Plano, TX · On-site

$55 - $60/hr

Implement RAG solutions using chunking, embeddings, vector databases, and retrieval techniques ... Apply prompt engineering techniques including system prompts, few-shot prompting, tool calling, and ...

Dotnet Developer

Coppell, TX · On-site

$44.75 - $59.25/hr

Net /Software Engineer, Irving, TX- 3 days in office- NO C2C, Onsite from Day one. POSITION SUMMARY ... RAG/Graph/LLMs are preferred • Bachelor's degree in Computer Science or related field required

Python + AI

Addison, TX · On-site

$48.75 - $67/hr

... Engineer to build LLM-based applications and AI APIs. The role involves working with Python and ... Responsibilities : • building LLM-based applications • building RAG pipelines • building AI ...

Agentic AI Developer

Irving, TX · On-site

$55 - $60/hr

This is an Agentic AI Developer role based in Irving, TX or Alpharetta, GA (100% Onsite) . The ... Vector Databases & RAG Hands-on experience with Pinecone, Qdrant, Milvus, Weaviate, or Chroma.

Develop andmaintainRetrieval-Augmented Generation (RAG)architecturesusing vector databases and ... Collaborate with product managers, engineers, and business stakeholders toidentifyopportunities for ...

AI Engineer

Irving, TX · On-site

$120K - $130K/yr

RAG; autonomous decision frameworks; Python/R/SQL/SAS; vector databases; semantic search; knowledge graphs; metadata management; production ML/AI deployment, monitoring, governance, explainability ...

Showing results 41-60

Rag Developer information

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.

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Infographic showing various Rag Developer job openings in Dallas, TX as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Other

Posted 8 days ago


Job description

We are seeking an AI Engineer to design and deploy production-grade AI solutions across LLM applications, RAG pipelines, retrieval systems, and scalable ML services.

This role blends model orchestration, search relevance, MLOps, and cross-functional collaboration to deliver reliable, high-impact AI products.

Responsibilities
Build and optimize LLM, RAG, and multi-agent workflows for production use cases.
Design retrieval systems using vector search, reranking, and metadata filtering.
Fine-tune, evaluate, and benchmark models to improve output quality and business impact.
Deploy AI/ML services with strong standards for latency, scalability, and observability.
Develop data, inference, and experimentation pipelines in partnership with product and engineering teams.

Required Qualifications
Strong Python and SQL skills with solid machine learning and NLP fundamentals.
Experience with LangChain, LangGraph, LlamaIndex, prompt engineering, and retrieval optimization.
Familiarity with vector databases and search tools such as Pinecone, OpenSearch, FAISS, or pgvector.
Experience with Docker, Kubernetes, MLflow, CI/CD, and cloud platforms such as Azure.