AI Applications Engineer

Responsibilities

• Design and develop AI applications using large language models (LLMs).
• Implement and manage AI agent systems using the CrewAI framework.
• Fine-tune language models for specific use cases and domain requirements.
• Build robust APIs and backend services using Python and FastAPI.
• Collaborate with cross-functional teams to integrate AI solutions into existing systems.
• Optimize model performance and implement best practices for AI application deployment.
• Research and evaluate new AI technologies and methodologies.
• Monitor and maintain AI systems in production environments.
• Document AI workflows, model architectures, and implementation details.
  

Requirements

• Strong proficiency in Python programming.
• Hands-on experience with large language models (LLMs) and their practical applications.
• Experience with model fine-tuning techniques and frameworks.
• Knowledge of AI agent systems, particularly the CrewAI framework.
• Understanding of machine learning workflows and model lifecycle management.
• Experience with API development and backend services.
• Strong problem-solving skills and ability to work with complex AI systems.
• Familiarity with AI/ML libraries and frameworks (transformers, langchain, etc. ).
  

Nice To Have

• Experience with FastAPI for building high-performance APIs.
• Docker containerization knowledge for AI application deployment.
• Understanding of prompt engineering and optimization techniques.
• Experience with vector databases and semantic search.
• Knowledge of MLOps practices and tools.
• Familiarity with cloud platforms (AWS, GCP, Azure) for AI workloads.
• Experience with other AI agent frameworks and orchestration tools.