Raleigh Hybrid Senior AI Engineer - RAG & Agentic AI

LexisNexis; Raleigh (NC); Hybrid; USD 105,000 - 175,000; Full time

Job summary

LexisNexis Legal & Professional in Raleigh, NC seeks an AI Engineer with deep RAG expertise and strong Python skills to develop next-generation AI solutions for professionals working with information and insights.

The role involves testing and deploying RAG models on AWS (SageMaker, Bedrock, Lambda, S3), advanced prompt engineering, and building agentic AI workflows with frameworks like LangGraph, AutoGen, or CrewAI. On-site/hybrid collaboration in a fast-paced, ethical AI environment.

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 ML frameworks like TensorFlow or PyTorch.
• Hands-on experience building agentic AI applications and cloud deployments.
• Familiarity with AWS services for AI/ML deployments.

Responsibilities

• Test, evaluate and implement AI models focusing on RAG.
• Strong prompt engineering and testing to achieve desired outcomes.
• Collaborate with cross-functional teams to integrate AI solutions.
• Optimize and fine-tune RAG models for performance and cost.
• Stay updated with latest advancements in AI/ML.
• Design, build, and deploy agentic AI systems using frameworks like LangGraph/AutoGen/CrewAI.
• Architect and deploy AI/ML/RAG solutions on AWS (SageMaker, Bedrock, Lambda, S3).
• Write clean, efficient Python code and perform data preprocessing.
• Troubleshoot AI models in mono-repo environments and document workflows.

Skills

Python

RAG models

Prompt engineering

ML frameworks

AWS cloud

Agentic AI

Communication

Tools

LangGraph

LangChain

AutoGen

CrewAI

AWS Bedrock Agents

Job description

LexisNexis Legal & Professional in Raleigh, NC seeks an AI Engineer with deep RAG expertise and strong Python skills to develop next-generation AI solutions for professionals working with information and insights.

The role involves testing and deploying RAG models on AWS (SageMaker, Bedrock, Lambda, S3), advanced prompt engineering, and building agentic AI workflows with frameworks like LangGraph, AutoGen, or CrewAI. On-site/hybrid collaboration in a fast-paced, ethical AI environment.