AI Engineer

Staffingine LLC; Charlotte (NC); On-site; USD 110,000 - 170,000; Full time

Job summary

Staffingine LLC in Charlotte, NC seeks an AI Engineer who will lead AI/ML initiatives with hands-on work and technical leadership. The role focuses on architecting, building, deploying, and optimizing enterprise AI solutions for production usage, including RAG, AI Agents, and semantic search.

The engineer will drive MLOps pipelines, cloud-native deployments on AWS, and scalable APIs using Python and FastAPI, coordinating with business and product stakeholders.

Qualifications

• 15+ years of software engineering experience.
• 5+ years building enterprise AI, ML, GenAI.
• Experience designing and deploying production-scale AI platforms.

Responsibilities

• Build GenAI applications using OpenAI, Claude, Gemini, Llama, and AWS Bedrock.
• Develop RAG solutions, AI Agents, semantic search, and MLOps pipelines.
• Create scalable APIs using Python and FastAPI; design AWS cloud-native architecture; implement CI/CD automation.

Skills

AI/ML Leadership

GenAI Applications

RAG systems

MLOps

Python

Tools

Python

FastAPI

AWS

CI/CD

Job description

Job Title: AI Engineer
Job Location: Charlotte, NC
Job Type: Full-Time

Job Description:

Experienced AI/ML and Data Engineering leader with 15+ years of software engineering experience and 5+ years building enterprise AI, Machine Learning, Generative AI, and cloud-native solutions. Strong hands-on expertise in designing and deploying production-scale AI platforms, RAG systems, AI Agents, MLOps frameworks, and cloud-native applications on AWS.

Role Overview

This role is primarily a 70% hands-on Individual Contributor and 30% technical leadership position. The engineer is expected to design, build, deploy, and optimize enterprise AI solutions while mentoring teams and coordinating with business, product, and engineering stakeholders.

Key Responsibilities

• Build GenAI applications using OpenAI, Claude, Gemini, Llama, and AWS Bedrock. Develop RAG solutions, AI Agents, semantic search, prompt engineering frameworks, and MLOps pipelines. Create scalable APIs using Python and FastAPI. Design cloud-native architecture using AWS services and implement CI/CD automation.