Chat Reader API

Role Overview:

We are seeking an experienced Python Developer to architect, design, and develop a
multi-agent Chat Reader API
. The ideal candidate will have deep expertise in Python, Large Language Models (LLMs), Natural Language Processing (NLP), and building scalable, distributed systems. You will play a key role in developing a system capable of understanding intent and context from human language, integrating multiple specialized agents, and providing robust API solutions.

Key Responsibilities:

• Design & Development:
  Architect, design, and implement a multi-agent Chat Reader API using Python. Develop specialized agents (e.g., Intent Reader, Context Reader) that collaborate effectively.
• LLM Integration:
  Integrate and fine-tune LLMs (e.g., GPT-4, LLaMA) to serve as the core intelligence of the agents for natural language understanding.
• Intent & Context Recognition:
  Develop advanced machine learning models for accurate intent recognition (e.g., feedback requests, assignment submissions, complaints) and context extraction.
• Fallback Mechanism:
  Implement resilient fallback systems to handle scenarios where primary agents fail, including rerouting chats to human agents or rule-based systems.
• API Development:
  Build and maintain scalable, secure, and well-documented RESTful APIs to expose Chat Reader functionality to other applications.
• Performance Optimization:
  Optimize the multi-agent system for speed and efficiency, reducing latency and managing computational resources.
• Testing & QA:
  Conduct rigorous testing protocols (unit, integration, and end-to-end) to validate accuracy, reliability, and robustness of the system.
• Collaboration:
  Work closely with product managers, data scientists, and front-end developers to define requirements and deliver a seamless end-to-end solution.

Required Skills & Expertise:

• Python Proficiency:
  Expert-level knowledge of Python, including modern frameworks and asynchronous programming.
• LLMs & NLP:
  Hands-on experience with Large Language Models, prompt engineering, fine-tuning, and libraries such as Hugging Face Transformers or LangChain.
• Multi-Agent Systems:
  Experience designing and implementing multi-agent architectures; familiarity with tools like CrewAI or AutoGen is a plus.
• API Development:
  Strong background in building and consuming RESTful APIs using FastAPI or Flask.
• Machine Learning:
  Solid understanding of ML concepts, especially classification and NLU, using frameworks like scikit-learn, TensorFlow, or PyTorch.
• System Architecture:
  Experience with microservices, distributed systems, and scalable architecture design.
• Data Management:
  Proficiency with SQL & NoSQL databases and handling large-scale chat data pipelines.

Preferred Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• Previous experience in chat-based applications, conversational AI, or multi-agent systems.