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.
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.
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 ...
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 ...
Develop and maintain Retrieval-Augmented Generation (RAG) architectures using vector databases and semantic search technologies * Create, test, and refine prompts, structured outputs, and evaluation ...
Develop and maintain Retrieval-Augmented Generation (RAG) architectures using vector databases and semantic search technologies * Create, test, and refine prompts, structured outputs, and evaluation ...
AI Engineer
Dallas, TX · On-site
Develop and maintain Retrieval-Augmented Generation (RAG) architectures using vector databases and semantic search technologies * Create, test, and refine prompts, structured outputs, and evaluation ...
AI Engineer
Dallas, TX · On-site
Develop and maintain Retrieval-Augmented Generation (RAG) architectures using vector databases and semantic search technologies * Create, test, and refine prompts, structured outputs, and evaluation ...
Design, develop, and implement enterprise AI applications utilizing Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG). * Develop AI-assisted search, summarization, and question ...
Design, develop, and implement enterprise AI applications utilizing Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG). * Develop AI-assisted search, summarization, and question ...
AI Engineer
Dallas, TX · On-site
Develop and maintain Retrieval-Augmented Generation (RAG) architectures using vector databases and semantic search technologies * Create, test, and refine prompts, structured outputs, and evaluation ...
Quick apply
AI Engineer
Dallas, TX · On-site
Develop and maintain Retrieval-Augmented Generation (RAG) architectures using vector databases and semantic search technologies * Create, test, and refine prompts, structured outputs, and evaluation ...
Design, develop, and implement enterprise AI applications utilizing Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG). * Develop AI-assisted search, summarization, and question ...
Design, develop, and implement enterprise AI applications utilizing Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG). * Develop AI-assisted search, summarization, and question ...
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 ...
Quick apply
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 ...
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 ...
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 ...
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 ...
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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 ...
Python Developer with LLM, GCP
Irving, TX · On-site
$48 - $66.25/hr
Advanced expertise in Prompt Engineering, fine-tuning, and Retrieval-Augmented Generation (RAG) techniques. Experience working with Vector databases and text embeddings. Experience within Google ...
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Python Developer with LLM, GCP
Irving, TX · On-site
$48 - $66.25/hr
Advanced expertise in Prompt Engineering, fine-tuning, and Retrieval-Augmented Generation (RAG) techniques. Experience working with Vector databases and text embeddings. Experience within Google ...
Engineer robust Retrieval-Augmented Generation (RAG) solutions that aggregate diverse business intelligence-spanning strategic client priorities, communication history, and value metrics-to ensure ...
Engineer robust Retrieval-Augmented Generation (RAG) solutions that aggregate diverse business intelligence-spanning strategic client priorities, communication history, and value metrics-to ensure ...
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 ...
New
Quick apply
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 ...
New
The ideal candidate will have hands-on experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, Azure AI services, Python, and enterprise AI platforms.
The ideal candidate will have hands-on experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, Azure AI services, Python, and enterprise AI platforms.
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 ...
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 ...
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 ...
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 ...
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 ...
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 ...
Engineer robust Retrieval-Augmented Generation (RAG) solutions that aggregate diverse business intelligence-spanning strategic client priorities, communication history, and value metrics-to ensure ...
Engineer robust Retrieval-Augmented Generation (RAG) solutions that aggregate diverse business intelligence-spanning strategic client priorities, communication history, and value metrics-to ensure ...
In this role, you will design, build, and enhance intelligent applications thatleverageLarge Language Models (LLMs), document processing pipelines, Retrieval-Augmented Generation (RAG) architectures ...
In this role, you will design, build, and enhance intelligent applications thatleverageLarge Language Models (LLMs), document processing pipelines, Retrieval-Augmented Generation (RAG) architectures ...
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:
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
About Prophecy Consulting
Sourced by ZipRecruiter
Company size
11 - 50 Employees
Headquarters location
Irvine, CA, US
Year founded
2018