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AI Engineer - Generative AI / Machine Learning

TrorCharlotte, NC🇺🇸United StatesPosted 2 Sept 2026

Why This Role Stands Out

This role offers a fantastic opportunity to build cutting-edge Generative AI solutions within an enterprise environment, leveraging your expertise in Python, LLMs, and cloud technologies. You'll thrive here if you have a strong background in AI/ML engineering and are eager to contribute to innovative projects that impact business operations. Join a dynamic team and advance your career in a leading technology company.

Quick Overview

Seniority
Mid Senior
Work mode
On Site
Location
Charlotte, NC, United States
Posted
22 hours ago
DockerFastAPISQLAWSMLOpsMachine LearningAzureGenerative AIGoogle CloudHugging FaceKubernetesLLMPyTorchPythonRESTTensorFlow

Job Description

Role: AI Engineer – Generative AI / Machine Learning

Location: Charlotte, NC (Onsite)

Experience: 7+ Years Overall | 3–4+ Years Hands-on AI/ML Engineering

 

 

Look for someone with Python + 3–4 yrs real AI/ML + GenAI/LLM + RAG + LangChain/LangGraph + Azure/Azure OpenAI + FastAPI + Vector DB/Embeddings + Docker/Kubernetes.
 
Role Overview
The client is looking for an AI Engineer with strong hands-on experience building and deploying production-grade AI/ML and Generative AI solutions in enterprise environments. The ideal candidate will have 7+ years of overall technology experience with at least 3–4 years of recent, real-world AI/ML engineering experience, preferably within banking or other highly regulated environments.
 
Key Responsibilities
  • Design, develop, and deploy AI/ML and Generative AI applications using Python.
  • Build LLM, RAG, semantic search, embeddings, and AI-agent solutions for enterprise use cases.
  • Develop AI services and APIs using Python/FastAPI and integrate models with enterprise applications.
  • Work with LangChain/LangGraph, OpenAI-compatible APIs, Hugging Face, and related AI/ML frameworks.
  • Build and optimize vector search/vector database solutions and retrieval pipelines.
  • Develop production-ready model deployment, monitoring, evaluation, and MLOps workflows.
  • Deploy AI workloads using Azure/AWS cloud services, with Azure experience preferred.
  • Work with Docker/Kubernetes and CI/CD for scalable AI application deployment.
  • Collaborate with data scientists, software engineers, architects, and business teams to move AI solutions from POC to production.
  • Follow enterprise standards for security, data privacy, responsible AI, governance, and model risk.
 
Required Skills
  • 7+ years of overall software/data/technology experience.
  • 3–4+ years of hands-on AI/ML Engineering experience on real production projects.
  • Strong Python programming and software engineering skills.
  • Hands-on Generative AI / LLM development experience.
  • Experience with RAG, embeddings, vector databases, semantic search, and prompt engineering.
  • Experience with LangChain and/or LangGraph.
  • Experience with OpenAI/Azure OpenAI or OpenAI-compatible APIs.
  • Experience developing AI services using FastAPI/REST APIs.
  • Strong understanding of ML model development, deployment, monitoring, and MLOps.
  • Cloud experience with Azure preferred; AWS/Google Cloud Platform acceptable.
  • Experience with Docker and Kubernetes.
  • Strong SQL and experience working with structured/unstructured enterprise data.
  • Banking/financial-services experience.
  • Experience with Azure AI Foundry, Microsoft Copilot/Copilot Studio, or agentic AI.
  • Experience with MCP, multi-agent orchestration, vLLM/Triton, or similar AI infrastructure.
  • Experience with PyTorch/TensorFlow or Hugging Face.
  • Experience working in highly regulated environments with AI governance, security, explainability, and model-risk controls.

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