Senior AI Engineer (Raleigh, NC)

LexisNexis; Raleigh (NC); Hybrid; USD 150,000 - 210,000; Full time

Job summary

LexisNexis is seeking an AI Engineer in Raleigh, NC, to drive Retrieval-Augmented Generation initiatives and deliver cutting-edge AI solutions. The role emphasizes Python development, model evaluation, and integration with existing systems across cross-functional teams.

The ideal candidate will have hands-on experience with RAG models, AWS services (SageMaker, Bedrock, Lambda, S3), and agentic AI frameworks for autonomous planning and multi-step execution. Hybrid on-site work is supported.

Qualifications

• Proven experience as an AI Engineer or similar role.
• Strong proficiency in Python programming.
• In-depth knowledge of Retrieval-Augmented Generation (RAG) models.
• Experience with ML frameworks such as TensorFlow or PyTorch.
• Hands-on experience with AWS services (SageMaker, Bedrock, Lambda, S3).

Responsibilities

• Test, evaluate and implement AI models with a focus on 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 cost savings.
• Design, build, and deploy agentic AI systems capable of autonomous planning, tool use, and multi-step task execution using 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.

Skills

Python

RAG

Prompt engineering

ML frameworks

Data preprocessing

Debugging

Teamwork

AWS

NLP

Git

Tools

AWS SageMaker

AWS Bedrock

AWS Lambda

S3

LangGraph

LangChain

AutoGen

CrewAI

Job description

PLEASE NOTE: This role is on-site/hybrid in Raleigh, NC

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.
• 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.