Senior AI Engineer (Raleigh, NC)

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.