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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
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Olivier Ludunge