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Entry Level Generative Ai Engineer Jobs in Raleigh, NC

Would you be excited to apply cutting-edge Generative AI technologies to solve complex, real-world ... Our team of AI scientists, consultants, and engineers works closely with customers to unlock ...

Would you be excited to apply cutting-edge Generative AI technologies to solve complex, real-world ... Our team of AI scientists, consultants, and engineers works closely with customers to unlock ...

... generative AI solutions with a flexible, multi-model approach that prioritizes using the best model ... About the Role As an AI Automation Engineer, you will design, build, and deploy AI-enabled ...

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Entry Level Generative Ai Engineer information

See Raleigh, NC salary details

$29.2K

$67.4K

$114.7K

How much do entry level generative ai engineer jobs pay per year?

As of Sep 7, 2026, the average yearly pay for entry level generative ai engineer in Raleigh, NC is $67,425.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,100.00 and $76,300.00 per year, depending on experience, location, and employer.

What is an entry level generative AI engineer?

Entry level generative AI engineers are professionals who work with artificial intelligence technologies focused on creating new content such as images, text, audio, or code. They typically assist in developing, training, and fine-tuning machine learning models like GPT or GANs under the supervision of senior engineers. These roles usually require a strong foundation in programming, mathematics, and machine learning concepts, but may not demand extensive industry experience. Tasks often include data preprocessing, model evaluation, and contributing to research or product development involving generative AI.

What are the key skills and qualifications needed to thrive as an entry level generative AI engineer?

To thrive as an Entry Level Generative AI Engineer, you need a solid background in computer science, mathematics, and machine learning fundamentals, typically supported by a relevant degree or coursework. Familiarity with Python, deep learning frameworks like TensorFlow or PyTorch, and version control systems such as Git is important, along with any foundational certifications in AI or data science. Strong problem-solving ability, curiosity, and effective teamwork skills will help you stand out in this collaborative and innovative field. These skills and qualities are crucial for developing, testing, and improving generative AI models in a rapidly evolving technical landscape.

What are common challenges faced by entry level generative AI engineers, and how can they be addressed?

Entry level Generative AI Engineers often encounter challenges such as mastering complex machine learning frameworks, understanding the nuances of training large models, and keeping up with rapidly evolving research. Collaborating closely with more experienced team members through code reviews and pair programming can accelerate learning. It's also helpful to engage in continuous education through online courses and participate in team discussions to stay updated on the latest advancements and best practices in the field.

What is the difference between Entry Level Generative Ai Engineer vs Data Scientist?

AspectEntry Level Generative Ai EngineerData Scientist
Required CredentialsBachelor's in CS, AI, or related field; basic knowledge of machine learning and programmingBachelor's or higher in CS, Statistics, or related; knowledge of data analysis and modeling
Work EnvironmentTech companies, AI startups, research labs focusing on AI model developmentVarious industries including finance, healthcare, marketing; analyzing data to inform decisions
Employer & Industry UsagePrimarily in AI and tech sectors developing generative modelsAcross multiple sectors using data to solve business problems

While both roles require a background in data and programming, Entry Level Generative Ai Engineers focus on developing AI models like generative adversarial networks, whereas Data Scientists analyze data to generate insights. The former is more specialized in AI model creation, while the latter covers broader data analysis tasks.

What are the most commonly searched types of Generative Ai Engineer jobs in Raleigh, NC?

The most popular types of Generative Ai Engineer jobs in Raleigh, NC are:

What are popular job titles related to Entry Level Generative Ai Engineer jobs in Raleigh, NC?

For Entry Level Generative Ai Engineer jobs in Raleigh, NC, the most frequently searched job titles are:

What job categories do people searching Entry Level Generative Ai Engineer jobs in Raleigh, NC look for?

The top searched job categories for Entry Level Generative Ai Engineer jobs in Raleigh, NC are:

Infographic showing various Entry Level Generative Ai Engineer job openings in Raleigh, NC as of August 2026, with employment types broken down into 91% Full Time, and 9% Contract. Highlights an 76% In-person, 6% Hybrid, and 18% Remote job distribution, with an average salary of $67,425 per year, or $32.4 per hour.

Sr AI Engineer (RAG Specialist with Strong Python Skills)

RELX Group plc

Raleigh, NC โ€ข On-site

$104K - $174K/yr

Full-time

Re-posted 20 days ago


Job description

*** PLEASE NOTE: This role is on-site/hybrid in Raleigh, NC ***
Are you passionate about building next-generation AI solutions that transform how professionals work with information and insights?
Do you thrive on solving complex challenges with Retrieval-Augmented Generation (RAG), agentic AI systems, and cloud-native machine learning technologies?
About our Team
LexisNexis Legal & Professional, which serves customers in more than 150 countries with 11,800 employees worldwide, is part of RELX (http://www.relx.com), a global provider of information-based analytics and decision tools for professional and business customers. Our company has been a long-time leader in deploying AI and advanced technologies to the legal market to improve productivity and transform the overall business and practice of law, deploying ethical and powerful generative AI solutions with a flexible, multi-model approach that prioritizes using the best model from today's top model creators for each individual legal use case. The company employs over 2,000 technologists, data scientists, and experts to develop, test, and validate solutions in line with RELX Responsible AI Principles (https://stories.relx.com/responsible-ai-principles/index.html).
About the Role
We are seeking a highly skilled AI Engineer with expertise in Retrieval-Augmented Generation (RAG) and strong Python programming skills to join our innovative team. The ideal candidate will have a deep understanding of AI and machine learning principles, experience with RAG models, and a passion for developing cutting-edge AI solutions.
Key Responsibilities:
  • Test, evaluate and and implement AI models with a focus on Retrieval-Augmented Generation (RAG).
  • Strong prompt engineering and prompt testing skills to derive the desired outcome
  • Collaborate with cross-functional teams to integrate AI solutions into existing systems.
  • Optimize and fine-tune RAG models for performance and scalability cost saving.
  • Conduct research and stay up-to-date with the latest advancements in AI and machine learning.
  • Design, build, and deploy agentic AI systems capable of autonomous planning, tool use, and multi-step task execution using frameworks such as LangGraph, AutoGen, or CrewAI.
  • Architect and deploy AI/ML and RAG solutions on AWS, leveraging services such as SageMaker, Bedrock, Lambda, and S3.
  • Write clean, efficient, and maintainable code in Python.
  • Perform data preprocessing, feature engineering, and model evaluation.
  • Troubleshoot and debug AI models and applications in a mono-repo settings.
  • Document AI models, processes, and workflows.

Qualifications:
  • Proven experience as an AI Engineer or similar role.
  • Strong proficiency in Python programming.
  • In-depth knowledge of Retrieval-Augmented Generation (RAG) models.
  • Proven experience in prompt engineering
  • Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch).
  • Proficiency in data preprocessing and feature engineering techniques.
  • Hands-on experience building agentic AI applications, including tool/function calling, multi-agent orchestration, and autonomous workflow design.
  • Demonstrated experience with AWS cloud services (e.g., SageMaker, Bedrock, Lambda, EC2, S3) for developing and deploying AI/ML solutions.
  • Excellent problem-solving skills and attention to detail.
  • Strong communication and teamwork abilities.

Preferred Skills:
  • Experience with cloud platforms, particularly AWS (e.g., SageMaker, Bedrock, Lambda, ECS/EKS, S3); familiarity with Azure or Google Cloud is a plus.
  • Experience with agentic AI frameworks and tooling (e.g., LangGraph, LangChain, AutoGen, CrewAI, AWS Bedrock Agents, Model Context Protocol).
  • AWS certification (e.g., AWS Certified Machine Learning - Specialty or AWS Certified Solutions Architect).
  • Knowledge of natural language processing (NLP) techniques.
  • Familiarity with version control systems (e.g., Git).
  • Experience with deploying AI models in production environments.

Work in a Way That Works for You
We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.
Working Pattern
Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive.
About the Business
LexisNexis Legal & Professionalยฎ provides legal, regulatory, and business information and analytics that help customers increase their productivity, improve decision-making, achieve better outcomes, and advance the rule of law around the world. As a digital pioneer, the company was the first to bring legal and business information online with its Lexisยฎ and Nexisยฎ services. #AIFluent
U.S. National Base Pay Range: $104,900 - $174,700. Geographic differentials may apply in some locations to better reflect local market rates.This job is eligible for an annual incentive bonus.
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