ZipRecruiter

Log In

1

Retrieval Augmented Generation Jobs in Dallas, TX

Prophecy Technologies

AI/ML Engineer

Plano, TX · On-site

$109K - $131K/yr

Fine-tune foundation models and implement Retrieval-Augmented Generation (RAG) architectures. * Develop REST APIs and microservices using FastAPI, Flask, or similar frameworks to expose AI models.

ClifyX

AI Architect

Plano, TX · On-site

GPT, Claude • Prompt Engineering • RAG (Retrieval Augmented Generation) • AWS Cloud • Strong architectural and hands on GenAI expertise • Experience with enterprise automation and testing ...

Pereview Software

AI Engineer

Dallas, TX · On-site

  • Medical

  • Dental

  • Vision

  • Retirement

Develop and maintain Retrieval-Augmented Generation (RAG) architectures using vector databases and semantic search technologies * Create, test, and refine prompts, structured outputs, and evaluation ...

Pereview Software

AI Engineer

Dallas, TX · On-site

  • Medical

  • Dental

  • Vision

  • Retirement

Develop and maintain Retrieval-Augmented Generation (RAG) architectures using vector databases and semantic search technologies * Create, test, and refine prompts, structured outputs, and evaluation ...

Pereview Software

AI Engineer

Dallas, TX · On-site

  • Medical

  • Dental

  • Vision

  • Retirement

Develop and maintain Retrieval-Augmented Generation (RAG) architectures using vector databases and semantic search technologies * Create, test, and refine prompts, structured outputs, and evaluation ...

Tata Consultancy Service Limited

Architect

Plano, TX · On-site

$120K - $130K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Implement RAG (Retrieval-Augmented Generation) patterns using requirements, user stories, APIs, configurations, and test repositories, leverage embeddings and vector search where applicable. Apply ...

Prolim Global

AI Architect - OT Cybersecurity

Plano, TX · On-site

Design AI-enabled solutions using technologies such as large language models, retrieval-augmented generation, semantic search, embeddings, vector databases, prompt engineering, workflow orchestration ...

Natsoft Corporation

Sierra.ai Consultant

Dallas, TX · On-site

... Retrieval-Augmented Generation (RAG) pipelines, and Agent SDKs - Skilled in building and deploying AI/LLM systems in production environments - Familiarity with AI agents, including evaluation ...

Delan Associates, Inc

AI Lead Engineer (Remote)

Dallas, TX · Remote

$104K - $138K/yr

Retrieval-Augmented Generation (RAG) * Embeddings & Vector Databases * Fine-tuning LLMs * Python * TensorFlow * PyTorch * Scikit-learn * Data Preprocessing & Feature Engineering * Model Training ...

ETS LLC

Senior AI Engineer

Dallas, TX · On-site

$103K - $142K/yr

Design and deliver LLM-powered applications, including agentic multi-step workflows, Retrieval-Augmented Generation (RAG) systems, and structured prompt pipelines. Productionize AI: Transform AI ...

Delan Associates, Inc.

AI Lead Engineer

Dallas, TX · On-site +1

$101K - $133K/yr

Retrieval-Augmented Generation (RAG) * Embeddings & Vector Databases * Fine-tuning LLMs * Python * TensorFlow * PyTorch * Scikit-learn * Data Preprocessing & Feature Engineering * Model Training ...

Delan Associates, Inc

AI Lead Engineer

Dallas, TX · Remote

$101K - $133K/yr

... Retrieval-Augmented Generation (RAG) Embeddings & Vector Databases Fine-tuning LLMs Python TensorFlow PyTorch Scikit-learn Data Preprocessing & Feature Engineering Model Training, Validation ...

next page

Showing results 1-20

All JobsRetrieval Augmented Generation JobsRetrieval Augmented Generation Jobs in Dallas, TX

Retrieval Augmented Generation information

What does a retrieval augmented generation engineer do?

A Retrieval Augmented Generation engineer typically spends their day designing and implementing systems that combine information retrieval with advanced generative models, such as large language models. This includes fine-tuning models, integrating external data sources, developing vector search pipelines, and evaluating output quality. Collaboration with data scientists, machine learning engineers, and product teams is common to ensure the solutions meet user requirements and scale effectively. Additionally, RAG engineers often troubleshoot issues, monitor model performance in production, and stay informed about the latest advancements in AI and information retrieval.

What is a retrieval augmented generation?

A Retrieval Augmented Generation (RAG) job typically involves developing and optimizing AI systems that enhance text generation by incorporating external knowledge retrieved from relevant sources. Professionals in this field work on integrating retrieval mechanisms with large language models to improve the relevance, accuracy, and factual grounding of generated content. Common responsibilities include designing retrieval systems, fine-tuning language models, optimizing performance, and ensuring the seamless integration of factual data into AI-generated text. This role is highly interdisciplinary, involving expertise in natural language processing (NLP), machine learning, and information retrieval.

What skills and qualifications are needed for retrieval augmented generation?

To thrive in a Retrieval Augmented Generation (RAG) engineering role, you need a solid background in machine learning, natural language processing (NLP), and experience with scalable information retrieval systems, typically supported by a relevant degree in computer science or a related field. Familiarity with tools such as Python, PyTorch or TensorFlow, vector databases, and search platforms like Elasticsearch is essential, along with practical experience deploying and tuning RAG pipelines. Strong problem-solving skills, a collaborative mindset, and effective communication abilities set outstanding professionals apart in this field. These competencies are crucial for designing, implementing, and optimizing hybrid retrieval-generation AI systems that address complex, real-world information needs.

What are the most commonly searched types of Retrieval Augmented Generation jobs in Dallas, TX?

The most popular types of Retrieval Augmented Generation jobs in Dallas, TX are:

What are popular job titles related to Retrieval Augmented Generation jobs in Dallas, TX?

For Retrieval Augmented Generation jobs in Dallas, TX, the most frequently searched job titles are:

What job categories do people searching Retrieval Augmented Generation jobs in Dallas, TX look for?

The top searched job categories for Retrieval Augmented Generation jobs in Dallas, TX are:

What cities near Dallas, TX are hiring for Retrieval Augmented Generation jobs?

Cities near Dallas, TX with the most Retrieval Augmented Generation job openings:

Retrieval Augmented Generation jobs near you
Infographic showing various Retrieval Augmented Generation job openings in Dallas, TX as of August 2026, with employment types broken down into 45% Full Time, and 55% Contract. Highlights an 74% In-person, and 26% Remote job distribution.

AI/ML Engineer

Prophecy Technologies

Plano, TX • On-site

$109K - $131K/yr

Full-time

Posted 24 days ago

Job description


AI/ML Engineer
?? Location: Plano, TX (Hybrid)
?? Duration: Long-Term Contract
Client: EmergerTech - USLBM
Job Overview
We are seeking a highly skilled AI/ML Engineer with strong expertise in Machine Learning, Deep Learning, Generative AI, and Large Language Models (LLMs) to design, build, and deploy enterprise-scale AI solutions. The ideal candidate will have hands-on experience developing production-ready AI applications, implementing MLOps best practices, and building scalable cloud-based machine learning systems.
This role offers the opportunity to work on cutting-edge AI initiatives, including Generative AI, Retrieval-Augmented Generation (RAG), LLM fine-tuning, and intelligent enterprise applications.
Key Responsibilities
  • Design, develop, train, and deploy scalable Machine Learning and Deep Learning models for production environments.
  • Build AI-powered applications using traditional ML techniques, Generative AI, and Large Language Models (LLMs).
  • Develop and optimize data pipelines for structured and unstructured data processing.
  • Fine-tune foundation models and implement Retrieval-Augmented Generation (RAG) architectures.
  • Develop REST APIs and microservices using FastAPI, Flask, or similar frameworks to expose AI models.
  • Build, automate, and maintain MLOps pipelines for model training, deployment, monitoring, and lifecycle management.
  • Collaborate with Data Scientists, Software Engineers, Data Engineers, and business stakeholders to deliver AI-driven solutions.
  • Optimize model accuracy, scalability, inference performance, and latency.
  • Implement AI governance, responsible AI practices, model monitoring, and security best practices.
  • Stay current with emerging AI technologies, frameworks, and industry trends.

Required Qualifications
  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
  • 10+ years of hands-on experience in Artificial Intelligence, Machine Learning, or Data Science.
  • Strong programming experience with Python.
  • Experience with Machine Learning frameworks including TensorFlow, PyTorch, and Scikit-learn.
  • Hands-on experience with Large Language Models (LLMs), Prompt Engineering, and Generative AI.
  • Experience implementing Retrieval-Augmented Generation (RAG) solutions.
  • Knowledge of vector databases such as Pinecone, FAISS, Chroma, or Milvus.
  • Experience with MLOps platforms such as MLflow, Kubeflow, SageMaker, or Vertex AI.
  • Experience building REST APIs using FastAPI, Flask, or similar frameworks.
  • Strong understanding of SQL and NoSQL databases.
  • Hands-on experience with Docker, Kubernetes, Git, and CI/CD pipelines.
  • Experience working with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.
  • Excellent analytical, communication, and problem-solving skills.

Preferred Qualifications
  • Experience with LangChain, LlamaIndex, or Semantic Kernel.
  • Experience working with Azure OpenAI, OpenAI APIs, Anthropic Claude, or Google Gemini.
  • Knowledge of distributed computing frameworks such as Apache Spark.
  • Experience with Databricks or Snowflake.
  • Familiarity with Responsible AI, AI Governance, and Model Monitoring.
  • AI/ML or Cloud certifications are a plus.

Technical Skills
  • Python
  • Machine Learning
  • Deep Learning
  • Generative AI
  • Large Language Models (LLMs)
  • Prompt Engineering
  • Retrieval-Augmented Generation (RAG)
  • LangChain / LlamaIndex
  • TensorFlow
  • PyTorch
  • Scikit-learn
  • FastAPI / Flask
  • Docker
  • Kubernetes
  • MLflow / Kubeflow
  • SQL / NoSQL
  • Vector Databases (Pinecone, FAISS, Chroma, Milvus)
  • REST APIs
  • Git
  • CI/CD
  • AWS / Azure / Google Cloud Platform

Apply