Retrieval Augmented Generation Rag Jobs in North Carolina

*** 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.

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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