Generative AI Engineer

Location

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