Artificial Intelligence Engineer

Cognio Labs is seeking a skilled Python Backend Engineer with expertise in FastAPI and a strong foundation in LLMs (Large Language Models) and RAG (Retrieval-Augmented Generation) technologies. This role combines backend development with data science to help us process data for fine-tuning and training models.

Core Technical Requirements

Essential Skills:

• Strong proficiency in Python backend development (2+ years of experience).
• Experience developing and maintaining APIs using the FastAPI framework.
• Knowledge of asynchronous programming and background task implementation.
• Proficiency in database management (SQL and NoSQL databases, particularly MongoDB).
• Experience with Git version control systems.
• Understanding of RESTful API design and implementation.

Additional Technical Skills:

• Experience with containerization technologies (Docker).
• Understanding of component-based architecture principles.
• Experience writing clean, maintainable, and testable code.
• Familiarity with testing frameworks and quality assurance practices.
  

AI & Data Science Requirements

• Experience with LLMs and RAG implementation is highly valued.
• Knowledge of data processing for fine-tuning language models.
• Understanding of data manipulation and analysis using Python libraries (Pandas, NumPy).
• Familiarity with AI technologies like LangChain, ChatGPT endpoints, and other LLM frameworks.
• Ability to implement and optimize machine learning workflows.
  

Key Responsibilities

• Design, develop, and maintain robust, scalable APIs using the FastAPI framework.
• Process and prepare data for fine-tuning and training language models.
• Implement background tasks and asynchronous processing to optimize system performance.
• Develop and integrate LLM and RAG-based solutions into our product ecosystem.
• Write efficient, maintainable code following industry best practices.
• Collaborate with team members on code reviews and knowledge sharing.
• Work with databases to design and implement data models and queries.
• Troubleshoot and debug issues in the existing codebase.
• Stay current with emerging technologies in Python development, LLMs, and data science.