2

Entry Level Retrieval Augmented Generation Jobs in Dallas, TX

Senior AI Engineer

Dallas, TX ยท 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 ...

Python Developer with ML - Dallas, TX

Dallas, TX ยท On-site

$49.75 - $68.50/hr

Develop and optimize Retrieval-Augmented Generation (RAG) pipelines for Large Language Models (LLMs) to provide contextually relevant and accurate outputs. This includes ingesting, processing, and ...

AI Engineer

Plano, TX ยท On-site

Develop Retrieval-Augmented Generation (RAG) applications using vector databases. * Create and consume REST APIs for AI services. * Design prompts and optimize AI model performance. * Work with cloud ...

Python Developer with ML - Dallas, TX

Dallas, TX ยท On-site

$49.75 - $68.50/hr

OOP, design patterns, modular architecture. โ€ข Develop and optimize Retrieval-Augmented Generation (RAG) pipelines for Large Language Models (LLMs) to provide contextually relevant and accurate ...

Sr Software Engineer AI-ML

Irving, TX ยท On-site

$113K - $149K/yr

... โ€ข Retrieval-Augmented Generation (RAG) โ€ข Model fine-tuning Company : Echo IT Solutions provides IT consulting, managed services, cloud, cybersecurity, data, and custom software development.

Build and optimize conversational agents, Retrieval-Augmented Generation (RAG) pipelines, and prompt engineering workflows. Collaboration: Communicate proactively with teammates, AI research ...

Build and optimize conversational agents, Retrieval-Augmented Generation (RAG) pipelines, and prompt engineering workflows. * Collaboration: Communicate proactively with teammates, AI research ...

Build and optimize conversational agents, Retrieval-Augmented Generation (RAG) pipelines, and prompt engineering workflows. * Collaboration: Communicate proactively with teammates, AI research ...

Build and optimize conversational agents, Retrieval-Augmented Generation (RAG) pipelines, and prompt engineering workflows. Collaboration: Communicate proactively with teammates, AI research ...

Build and optimize conversational agents, Retrieval-Augmented Generation (RAG) pipelines, and prompt engineering workflows. * Collaboration: Communicate proactively with teammates, AI research ...

Experience with LLMs, generative AI, NLP, retrieval-augmented generation (RAG), or prompt orchestration frameworks. * Experience designing multi-cloud application architectures and integration ...

Experience with Large Language Models (LLMs) , Generative AI , Natural Language Processing (NLP) , Retrieval-Augmented Generation (RAG) , or prompt orchestration frameworks. * Experience designing ...

next page

Showing results 1-20

Entry Level Retrieval Augmented Generation information

What is an entry level retrieval augmented generation job?

Entry level retrieval augmented generation jobs involve assisting in the development and optimization of AI systems that combine information retrieval techniques with generative models. Employees in these roles typically help build, test, and maintain systems where AI retrieves relevant data from large databases to enhance the accuracy and relevance of generated responses. These positions often require basic skills in programming, machine learning, and familiarity with natural language processing. They are ideal for recent graduates or those new to AI, offering opportunities to learn about modern AI architectures and contribute to innovative projects. Entry level workers may work under the guidance of senior engineers or researchers, supporting experimentation and evaluation tasks.

What are the key skills and qualifications needed to thrive as an entry level retrieval augmented generation specialist?

To thrive as an Entry Level Retrieval Augmented Generation Specialist, you need a foundational understanding of natural language processing (NLP), information retrieval, and basic programming skills, often supported by a degree in computer science or a related field. Familiarity with tools such as Python, vector databases (like FAISS or Pinecone), and frameworks for large language models (LLMs) is typically required. Strong problem-solving abilities, attention to detail, and effective communication help you collaborate and troubleshoot solutions in team environments. These skills and qualities are crucial for building reliable RAG systems that deliver accurate and relevant information to users.

What is the difference between Entry Level Retrieval Augmented Generation vs Entry Level Data Scientist?

AspectEntry Level Retrieval Augmented GenerationEntry Level Data Scientist
Required CredentialsBasic programming, understanding of NLP and AI conceptsBachelor's in Data Science, Computer Science, or related field
Work EnvironmentTech companies, AI startups, research labsTech firms, finance, healthcare, consulting
Industry UsageAI development, NLP applications, chatbot creationData analysis, predictive modeling, data-driven decision making

Entry Level Retrieval Augmented Generation focuses on developing AI models that combine retrieval techniques with generative AI, requiring knowledge of NLP and programming. Entry Level Data Scientist involves analyzing data, building models, and deriving insights, often with a broader data analysis skill set. While both roles require technical skills, Retrieval Augmented Generation is more specialized in AI model development, whereas Data Scientists work across various data projects.

What are some common challenges faced by entry-level professionals working in retrieval augmented generation roles?

Entry-level professionals in Retrieval Augmented Generation (RAG) often encounter challenges such as understanding how to effectively combine information retrieval systems with large language models and adapting to rapidly evolving technologies. Balancing accuracy and efficiency when designing or fine-tuning retrieval pipelines can also be a learning curve. Additionally, you may need to collaborate closely with data engineers, machine learning specialists, and product teams to ensure the RAG system aligns with business requirements. Staying proactive in learning and engaging with peers can help overcome these challenges and accelerate career growth.
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 Entry Level Retrieval Augmented Generation jobs in Dallas, TX? For Entry Level Retrieval Augmented Generation jobs in Dallas, TX, the most frequently searched job titles are:
What job categories do people searching Entry Level Retrieval Augmented Generation jobs in Dallas, TX look for? The top searched job categories for Entry Level Retrieval Augmented Generation jobs in Dallas, TX are:
Infographic showing various Entry Level Retrieval Augmented Generation job openings in Dallas, TX as of August 2026, with employment types broken down into 73% Full Time, 25% Part Time, and 2% Contract. Highlights an 67% Physical, 2% Hybrid, and 31% Remote job distribution.

Python Developer with LLM, GCP

Sparc Technology Services Inc

Irving, TX โ€ข On-site

$48 - $66.25/hr

Full-time

Re-posted 21 days ago


Job description

Python Developer – data engineering – GCP – Working 
Exp with LLMs etc
building custom Python applications for large-scale data 
building pipelines for data processing and deploying in GCP 
Solid foundation in Machine Learning
Extensive experience working with Large Language Models (LLMs) such as Gemini, Claude, and GPT with in-depth understanding of tokenization, embeddings, and context management.
Advanced expertise in Prompt Engineering, fine-tuning, and Retrieval-Augmented Generation (RAG) techniques.
Experience working with Vector databases and text embeddings.
Experience within Google Cloud environments (e.g., BigQuery, Cloud Run).

Flexible work from home options available.