Generative AI Engineer

Location

Dallas, TX (or) Charlotte, NC (or) Raleigh, NC

US Citizens and Green Card Holders needed

Role Overview

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) , prompt engineering , and 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), and multi modal AI solutions while integrating GenAI capabilities into production-grade applications and workflows.

Mission

Design and deliver scalable, production-ready Generative AI solutions that leverage modern LLMs, agentic frameworks, and cloud AI platforms to power intelligent applications across the enterprise.

Key Responsibilities (Scope)

• Design and implement Generative AI models for:
  

  • Text-based applications
    

  • Image-based applications
    

  • Multimodal AI solutions
    

• Develop and optimize prompt engineering strategies to improve LLM performance and reliability
  

• Build and integrate embedding-based retrieval systems and RAG pipelines
  

• Integrate Generative AI capabilities into web applications and enterprise workflows
  

• Design and develop agentic AI applications with:
  

  • Context management
    

  • Session and memory handling
    

  • MCP (Model Context Protocol) tools
    

• Collaborate with cross-functional teams to deploy AI solutions at scale
  

• Ensure AI solutions are reliable, secure, and production-ready
  

Required Qualifications

• Strong proficiency in Python
  

• Solid experience with AI/ML frameworks such as:
  

  • PyTorch
    

  • TensorFlow
    

• Hands-on experience building multi-agent systems , including:
  

  • Session management
    

  • Memory handling
    

  • MCP tools
    

• Practical experience working with:
  

  • Large Language Models (LLMs)
    

  • Transformer architectures
    

  • Hugging Face ecosystem
    

• Knowledge and experience with:
  

  • Vector databases
    

  • Retrieval-Augmented Generation (RAG)
    

  • Semantic search techniques
    

• Familiarity with cloud AI services , including:
  

  • AWS SageMaker
    

  • Azure OpenAI
    

  • GCP Vertex AI
    

• Understanding of MLOps practices for scalable AI deployment
  

Preferred Qualifications

• Knowledge of AI ethics , including:
  

  • Bias mitigation
    

  • Responsible AI practices
    

• Experience designing AI systems with governance, transparency, and compliance in mind