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Entry Level Retrieval Augmented Generation Jobs (NOW HIRING)

Concord Advice

Data Scientist Intern

Florham Park, NJ · On-site

Working knowledge of modern AI application patterns, including retrieval-augmented generation (RAG) and AI-assisted automation. * • Outstanding communication skills (both technical and non ...

Noblesoft Technologies

AI Developer

San Jose, CA · Remote

Integrate memory systems and RAG (Retrieval-Augmented Generation) using vector databases for context management. * Ensure agent reliability, safety, and governance by establishing robust guardrails ...

Palnar

ONLY W2 | AI Engineer@ Denver, Co

Denver, CO · On-site

Solid understanding of LLM architectures, embeddings, and retrieval-augmented generation (RAG). * Proficiency in Python, JavaScript/TypeScript , or similar programming languages. * Experience with ...

Vkore Solutions

GenAI Engineer-W2

Austin, TX · On-site

Familiarity with retrieval-augmented generation (RAG) and prompt engineering. * Strong problem-solving skills and ability to work in fast-paced AI environments. Preferred: * Experience with open ...

USM

JB061726 - AI Developer

Charlotte, NC · On-site

Develop Retrieval-Augmented Generation (RAG) systems using vector databases. * Collaborate with product managers, designers, and software engineers to deliver AI features. * Fine-tune and evaluate ...

Photon

Python Developer with ML - Dallas, TX

Dallas, TX

$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 ...

Proximate Technologies Inc.

AI/ML Engineer

Plano, TX · On-site

Apply retrieval augmented generation (RAG) techniques to data to populate and query vector databases (e.g. Weaviate) * Build custom applications with LLM frameworks such as LangChain, DSPy ...

2T Consulting

AI Agent Engineer

Louisville, KY · On-site

Develop and maintain Retrieval-Augmented Generation (RAG) pipelines for enterprise-scale applications. * Architect scalable backend services and APIs to support AI-driven products. * Collaborate with ...

Intraedge

Senior AI Developer

Phoenix, AZ · On-site

$54 - $71.50/hr

Design and implement GenAI applications using Retrieval-Augmented Generation (RAG) in production settings. Build and optimize document ingestion pipelines and document processing workflows utilizing ...

Tallgrass

AI System Developer I

Lakewood, CO · On-site

The AI System Developer I serves as an entry-level individual contributor responsible for ... Learn and apply retrieval-augmented generation (RAG) concepts including vector stores and knowledge ...

New

AAIT Health

AI Engineer

Little Rock, AR · On-site

Implement retrieval-augmented generation (RAG) and clinical knowledge workflows that query patient context, incorporate medical reference content, and cite sources with traceability. * Engineer ...

Nastech Global

GCP Gen AI Architect

Boston, MA · On-site

Build Retrieval-Augmented Generation (RAG) pipelines to improve the quality of AI-generated responses. Collaborate with various stakeholders to integrate and deploy AI models into production ...

AAIT Health LLC

AI Engineer

Little Rock, AR

Implement retrieval-augmented generation (RAG) and clinical knowledge workflows that query patient context, incorporate medical reference content, and cite sources with traceability. * Engineer ...

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Entry Level Retrieval Augmented Generation information

What are entry level retrieval augmented generation jobs?

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, and why are they important?

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 (RAG) 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.
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Entry Level Retrieval Augmented Generation jobs near you
Infographic showing various Entry Level Retrieval Augmented Generation job openings in the United States as of July 2026, with employment types broken down into 28% Locum Tenens, 64% Full Time, 6% Part Time, and 2% Contract. Highlights an 77% Physical, 3% Hybrid, and 20% Remote job distribution.
W2 role || Generative AI Engineer New York City, NY Hybrid - In person Interview

W2 role || Generative AI Engineer New York City, NY Hybrid - In person Interview

HAN IT Staffing Inc.

Manhattan, NY • On-site

Other

Posted yesterday

New

Job description

We are seeking a highly skilled Generative AI Engineer with expertise in Large Language Models (LLMs), Python, Retrieval-Augmented Generation (RAG), and Agent Orchestration to design, build, and optimize next-generation AI solutions. In this role, you will work at the forefront of AI innovation, developing intelligent systems that enhance user experiences, automate business workflows, and deliver scalable AI-powered products.
You will collaborate closely with cross-functional teams including data scientists, software engineers, product managers, and business stakeholders to bring generative AI applications from concept to production. The ideal candidate has hands-on experience with LLMs, prompt engineering, orchestration frameworks, model evaluation, and deploying AI solutions in cloud environments.
Key Responsibilities
  • Design, develop, fine-tune, and optimize large language models (LLMs) for a wide range of business and product use cases.
  • Build and deploy generative AI applications using Python and AI/ML frameworks such as PyTorch, TensorFlow, and Hugging Face Transformers.
  • Develop Retrieval-Augmented Generation (RAG) pipelines by integrating vector databases, embeddings, semantic search, and knowledge retrieval systems.
  • Implement and manage agent orchestration workflows using frameworks such as LangChain, LlamaIndex, AutoGen, CrewAI, or similar multi-agent systems.
  • Conduct data preprocessing, feature engineering, and dataset preparation to support model training, fine-tuning, and evaluation.
  • Collaborate with engineering and product teams to integrate AI models and agent-based systems into production-grade applications and APIs.
  • Evaluate model and system performance using relevant metrics, and continuously improve accuracy, latency, scalability, and cost efficiency.
  • Design prompt strategies, guardrails, and monitoring approaches to ensure reliable and safe LLM outputs.
  • Stay current with the latest advancements in generative AI, LLM architecture, RAG, AI agents, and emerging research trends.
  • Ensure compliance with ethical AI principles, security standards, and data privacy regulations throughout the AI development lifecycle.
Required Qualifications
  • Proven experience in developing, fine-tuning, and deploying large language models such as GPT, BERT, T5, LLaMA, or similar architectures.
  • Strong programming skills in Python with experience building AI/ML solutions in production environments.
  • Hands-on experience with AI/ML frameworks such as PyTorch, TensorFlow, and Hugging Face.
  • Solid understanding of natural language processing (NLP) concepts, prompt engineering, model evaluation, and fine-tuning techniques.
  • Experience designing and implementing RAG architectures, including embeddings, vector stores, document chunking, retrieval strategies, and grounding mechanisms.
  • Familiarity with agent orchestration frameworks and building multi-step or multi-agent AI workflows.
  • Experience with API development, microservices, and integrating AI capabilities into enterprise systems.
  • Working knowledge of cloud platforms such as AWS, Google Cloud Platform, or Azure for scalable AI deployment.
  • Strong analytical thinking, problem-solving ability, and effective collaboration skills.
  • Bachelor s or Master s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field. Ph.D. is a plus.
Preferred Skills
  • Experience deploying and managing LLM applications with MLOps/LLMOps practices, including monitoring, versioning, and experimentation.
  • Familiarity with vector databases such as Pinecone, Weaviate, FAISS, Chroma, or Milvus.
  • Knowledge of Docker, Kubernetes, CI/CD pipelines, and scalable deployment patterns for AI services.
  • Experience with cloud-native AI services and model hosting infrastructure.
  • Understanding of AI safety, model governance, observability, and responsible AI practices.
  • Knowledge of additional programming languages is a plus.
  • Strong publication record, research background, or contributions to open-source AI projects
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About Han Staffing

Sourced by ZipRecruiter

HAN Staffing was born in 2012, out of the real world experience of individuals who worked in the trenches of the Recruitment Industry. Individuals who have staffed at some of the biggest names in Finance, Retail, Hospitality, Healthcare, Financial and Business Consulting as well as small Businesses. In the last five years, we have witnessed 200% growth and an always increasing roster of Satisfied Clients, thanks to our never say die Recruiting attitude. We are the only Staffing Company who stay by your side until the very end, with a leadership team that is available 24/7. Our goal is to work as a trusted adviser and partner to your business, adding value to your Recruitment efforts. Whether you are a large Corporation or a Small Business trying to find the perfect talent, we serve you with passion and perseverance to meet your needs with excellence.

Industry

Recruiting and staffing services

Company size

11 - 50 Employees

Headquarters location

Iselin, NJ, US

Year founded

2012

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