Generative AI Engineer

Dallas TX or Charlotte NC or Raleigh NC

We are seeking a highly skilled Generative AI Engineer with a strong Python background to design develop and deploy cutting-edge AI solutions. The ideal candidate will have hands-on experience with Large Language Models (LLMs) Vision Language Models (Vision LLMs/VLMs) vLLM inference framework prompt engineering and modern Generative AI frameworks along with proven expertise in building scalable AI applications for enterprise use cases.

This role focuses on developing Agentic AI systems Retrieval-Augmented Generation (RAG) multimodal AI solutions and high-performance LLM inference while integrating GenAI capabilities into production-grade enterprise applications.

Design and deliver scalable production-ready Generative AI solutions leveraging modern LLMs Vision LLMs Agentic AI frameworks RAG architectures and cloud AI platforms to power intelligent enterprise applications.

• Text-based AI applications
  
• Image-based AI applications
  
• Vision Language Models (Vision LLMs)
  
• Multimodal AI applications
  

• Develop and optimize advanced prompt engineering strategies to improve LLM performance accuracy and reliability.
  
• Build and integrate embedding-based retrieval systems and Retrieval-Augmented Generation (RAG) pipelines.
  
• Design and implement Agentic AI applications including:
  
  • Context management
    
  • Session and memory handling
    
  • MCP (Model Context Protocol)
    
  • Tool calling and workflow orchestration
    
• Deploy and optimize vLLM for high-throughput low-latency LLM inference in production environments.
  
• Build scalable APIs using Python and integrate GenAI capabilities into enterprise applications and workflows.
  
• Collaborate with cross-functional teams to deploy AI solutions at scale.
  
• Ensure AI solutions are secure scalable reliable and production-ready.
  

• Strong proficiency in Python
  

• Solid experience with AI/ML frameworks including:
  
  • PyTorch
    
  • TensorFlow
    

Hands-on experience building multi-agent AI systems including:

• Session management
  
• Memory handling
  
• MCP (Model Context Protocol)
  
• Tool integration and orchestration
  

Practical experience with:

• Large Language Models (LLMs)
  
• Vision Language Models (Vision LLMs / VLMs)
  
• Transformer architectures
  
• Hugging Face ecosystem
  
• vLLM for optimized LLM serving and inference
  

Experience with:

• Vector databases
  
• Embeddings
  
• Retrieval-Augmented Generation (RAG)
  
• Semantic Search
  

Experience with one or more:

• AWS SageMaker
  
• Azure OpenAI
  
• Google Vertex AI
  

• Understanding of MLOps and LLMOps practices
  
• Experience deploying scalable AI applications in production
  

• Experience with multimodal AI systems combining text images and documents
  
• Knowledge of AI ethics including:
  
  • Bias mitigation
    
  • Responsible AI practices
    
• Experience designing AI systems with governance transparency and compliance in mind
  
• Experience with distributed GPU inference model optimization quantization and high-performance AI serving
  
• Familiarity with frameworks such as LangChain LangGraph LlamaIndex CrewAI or AutoGen