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Entry Level Retrieval Augmented Generation Jobs (NOW HIRING)

Accord Technologies Inc.

GEN AI Architect

New York, NY · On-site

The ideal candidate will have a strong background in investment banking, hands-on experience with Microsoft Azure OpenAI, and expertise in Retrieval-Augmented Generation (RAG). Key Responsibilities:

WelbeHealth

AI Engineer I

Working under the guidance of senior engineers, the role assists with developing and maintaining enterprise AI models, retrieval-augmented generation (RAG) systems, and agentic workflows. The AI ...

ClifyX

Senior Agentic AI Builder

San Jose, CA · On-site

$107K - $136K/yr

... retrieval-augmented generation pipelines for context-aware AI applications • MCP (Model Context Protocol) - Practical experience with MCP client/server patterns for structured tool-to-data ...

Tekshapers Inc

Generative AI/ML Engineer

New York, NY · On-site

The ideal candidate will have a strong background in investment banking, hands-on experience with Microsoft Azure OpenAI, and expertise in Retrieval-Augmented Generation (RAG). Key Responsibilities:

Concord Advice

Data Scientist - Intern

Florham Park, NJ · On-site

$40K - $70K/yr

Our strategic investments in cloud infrastructure and MLOps pipelines enable us to leverage state-of-the-art language AI -- from large-language-model (LLM) agents and retrieval-augmented generation ...

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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 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 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.

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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 September 2026, with employment types broken down into 1% Internship, 68% Full Time, 30% Part Time, and 1% Contract. Highlights an 63% Physical, 2% Hybrid, and 35% Remote job distribution.

Senior AI Engineer - LLM Systems & RAG Optimization

Remote

Texas Sports Academy
See more jobs at Texas Sports Academyexternal

Contractor

Re-posted 10 days ago

Job description

Texas Sports Academy is on the lookout for a Senior AI Engineer specializing in LLM (Large Language Model) Systems and RAG (Retrieval-Augmented Generation) Optimization. As we continue to push the boundaries of sports technology, your role will be pivotal in developing and optimizing AI-driven solutions that enhance our offerings for athletes and coaches. You will be responsible for designing, developing, and fine-tuning LLM systems that can offer personalized insights and performance recommendations based on data-driven analysis. Your expertise in retrieval-augmented generation will enable the integration of comprehensive data sources, empowering our systems to deliver high-quality, context-aware content and responses. You will work collaboratively with data scientists, software engineers, and domain experts to implement scalable AI solutions that drive innovation in our training programs. If you are passionate about harnessing the power of AI to transform the sports industry and have a strong foundation in NLP and machine learning, this is the perfect opportunity for you to make an impact.
Responsibilities
  • Design and implement LLM systems tailored to the needs of athletes and coaches.
  • Optimize retrieval-augmented generation processes to improve the quality and relevance of AI-generated content.
  • Collaborate with cross-functional teams to define AI strategies and ensure alignment with business goals.
  • Conduct research on cutting-edge AI methodologies and integrate them into existing systems.
  • Monitor and evaluate system performance, making data-driven adjustments as necessary.
  • Mentor junior team members and help cultivate a culture of innovation within the department.
  • Document system architecture, processes, and best practices for future reference and team knowledge sharing.

Requirements
  • Master's degree or Ph.D. in Computer Science, Artificial Intelligence, or a related field.
  • Extensive experience with Large Language Models (LLMs) and retrieval-augmented generation systems.
  • Proficient in programming languages such as Python, with a strong understanding of data structures and algorithms.
  • Familiarity with AI/machine learning frameworks (e.g., TensorFlow, PyTorch) and NLP libraries.
  • Experience with optimizing AI models for efficiency and performance.
  • Strong analytical and problem-solving skills with the ability to work effectively in a fast-paced environment.
  • Exceptional communication skills to articulate complex concepts to stakeholders and team members.

Apply