The AI Engineer – NLP is a hands-on, onsite role in Charlotte focused on building, deploying, and supporting production-grade LLM applications. The position requires strong Python backend engineering, RAG, orchestration frameworks, agents/tool calling, guardrails, evaluation, and PostgreSQL-backed services. The engineer will use Azure or comparable cloud platforms to design scalable, secure, and reliable AI solutions. Candidates must understand real-world trade-offs involving model quality, latency, cost, security, and performance. This is not a research-focused position; it requires ownership of live applications, production troubleshooting, and the ability to deliver results with limited oversight. AI Engineer NLP – Benefits: • Health, dental, and vision insurance • Paid time off and holidays • 401(K) retirement savings plan options • Opportunities for career advancement and professional growth AI Engineer NLP - Required Qualifications: • Deep hands-on experience building and supporting production LLM applications. • Strong Python backend engineering experience. • Experience with PostgreSQL or another robust relational DBMS. • Hands-on experience with RAG, embeddings, semantic retrieval, and vector search. • Strong understanding of orchestration frameworks such as LangChain, LangGraph, or comparable tools. • Experience with agents, tool/function calling, guardrails, and response validation. • Ability to design appropriate architectural patterns for real-world business problems. • Experience deploying scalable AI solutions in Azure; strong AWS or GCP experience may also be considered. • Experience managing production concerns including latency, cost, security, reliability, monitoring, and incidents. • Ability to work independently, take ownership, and deliver results with limited oversight. • Authorized to work in the United States without current or future sponsorship. • Able to work onsite in Charlotte, North Carolina. AI Engineer NLP – Preferred Skills: • React or other modern front-end development experience. • DevOps and Infrastructure as Code experience, including Terraform or comparable tools. • Docker, Kubernetes, and CI/CD pipeline experience. • Traditional machine learning experience in addition to LLM engineering. • Experience with Azure AI services and cloud-native deployment patterns. • Familiarity with observability, model monitoring, and production support tooling. • Experience with vector databases, embeddings, and retrieval optimization. • Knowledge of secure AI application design, prompt-injection defenses, and access controls. JOB ID: 179217 #post Olivier Ludunge