Principal AI Engineer GenAI / Agentic Systems

AI Engineer GenAI / Agentic Systems

Location: Charlotte, NC or Dallas, TX

Need hands-on experience with Vision Language Models (VLMs).

About the Role

We are seeking an experienced AI Engineer to design, build, and deploy production-grade GenAI solutions. This role focuses on developing agentic AI systems, GraphRAG applications, and enterprise LLM services that solve real business problems.

The ideal candidate has hands-on experience taking GenAI applications from proof of concept into production, enjoys working with modern agent development frameworks, and stays current with the rapidly evolving GenAI ecosystem.

What You'll Do

• Design, build, and deploy production-grade GenAI applications leveraging foundation models and advanced architectures such as GraphRAG.
• Develop autonomous AI agents using modern agent development frameworks such as Google ADK, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar technologies.
• Take AI solutions from prototype through production deployment, ensuring scalability, reliability, observability, and maintainability.
• Design and implement advanced RAG and GraphRAG pipelines that integrate enterprise knowledge sources using embeddings and knowledge graphs.
• Build scalable REST APIs using Python (FastAPI) that power LLM-driven enterprise applications.
• Containerize and deploy AI services using Docker and cloud platforms including AWS, Azure, or Google Cloud Platform.
• Implement LLM evaluation frameworks using LangSmith, Ragas, DeepEval, or custom evaluation pipelines to measure answer quality, groundedness, latency, and hallucination rates.
• Apply LLMOps best practices including CI/CD, prompt/version management, automated testing, monitoring, and production observability.
• Collaborate with engineering teams to integrate AI capabilities into enterprise platforms.
• Mentor engineers and contribute to technical best practices for GenAI application development.
• Stay current with emerging GenAI technologies, agent frameworks, and industry best practices, evaluating new tools and approaches as the ecosystem evolves.

What You'll Bring

• Bachelor's degree in Computer Science or a related technical field (or equivalent practical experience).
• 5+ years of software engineering experience, including recent experience building GenAI or LLM-powered applications.
• Demonstrated experience taking GenAI applications from proof of concept into production.
• Hands-on experience with one or more modern agent development frameworks such as Google ADK, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar.
• Strong Python development skills, including FastAPI and REST API design.
• Experience implementing RAG or GraphRAG solutions using embeddings, vector databases, knowledge graphs, and enterprise data sources.
• Experience deploying AI workloads using Docker and AWS, Azure, or Google Cloud Platform.
• Familiarity with LLMOps practices including CI/CD, prompt management, model/version governance, monitoring, and evaluation.
• Experience with LLM evaluation tools such as LangSmith, Ragas, DeepEval, or equivalent frameworks.
• Strong communication, collaboration, and problem-solving skills.
• Demonstrated curiosity and commitment to staying current with the rapidly evolving GenAI and agentic AI landscape.