Lead AI Engineer: RAG & LLM Solutions (Hybrid)

Experis Technology Group; Charlotte (NC); Hybrid; USD 103,000 - 117,000; Full time

Benefits offered by this job

Medical plan

Dental plan

Vision plan

Health Savings Account

Health Flexible Spending Account

Dependent Care Flexible Spending Order

Supplemental Life Insurance

Short Term Disability Insurance

Long Term Disability Insurance

Business Travel Insurance

401(k) with match

Weekly Pay

Job summary

Experis Technology Group seeks a Lead AI Engineer in Charlotte, NC to guide the AI Engineering group and deliver production-grade AI solutions. You will design, implement, and monitor AI applications using Python, LLMs, and enterprise APIs for real-world business needs.

You will lead discussions, mentor engineers, and collaborate with stakeholders to translate requirements into reliable, scalable AI systems. A hybrid onsite schedule applies in Charlotte.

Qualifications

• 5+ years Python experience.
• 3+ years building production REST APIs.
• 2+ years leading solution architecture and engineering delivery.
• 2+ years deploying applications on cloud infrastructure.

Responsibilities

• Design and develop AI applications using Python, LLMs, and enterprise APIs.
• Build and improve retrieval-augmented generation (RAG) pipelines, including document ingestion, embeddings, and vector search.
• Evaluate AI responses for accuracy, reliability, latency, and cost; troubleshoot issues and drive improvements.
• Lead technical discussions, mentor engineers, and collaborate with stakeholders to prioritize delivery.

Skills

Python programming

REST APIs

LLMs

RAG pipelines

Embeddings

Vector databases

Cloud deployment

Tools

Python

APIs

Job description

Experis Technology Group seeks a Lead AI Engineer in Charlotte, NC to guide the AI Engineering group and deliver production-grade AI solutions. You will design, implement, and monitor AI applications using Python, LLMs, and enterprise APIs for real-world business needs.

You will lead discussions, mentor engineers, and collaborate with stakeholders to translate requirements into reliable, scalable AI systems. A hybrid onsite schedule applies in Charlotte.