Published on April 27, 2025. Modified on May 13, 2025.
Key Responsibilities
• Develop and maintain Conversational AI applications using Python, focusing on RAG (Retrieval-Augmented Generation) architectures.
• Integrate AI models with external data sources using Langchain for dynamic response generation. • Utilize AI/ML services for deploying large language models (LLMs) and other AI components.
• Build and optimize data pipelines to feed models with relevant, real-time data for efficient AI-driven conversations.
• Ensure code quality, performance, and scalability in production environments.
• Maintain thorough documentation and testing for developed modules and systems.
• Education: Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.
Qualifications & Experience
•Experience: 3+ years of experience in Python development, including experience working with AI and machine learning frameworks.
• Technical:
• Hands-on experience with RAG (Retrieval Augmented Generation) and knowledge of integrating retrieval systems with generative models.
• Basic understanding of Langchain and its usage for building conversational AI applications.
• Experience working with message queues (e.g., Rabbit MQ, Kafka) for handling large-scale real-time data processing.
• Experience with RESTful APIs, microservices architecture, and distributed systems.
• Proficient with version control (Git), Docker, and containerized applications.
• Familiarity with cloud platforms, particularly AWS, and experience with deploying applications in cloud environments.
• Soft Skills: Strong problem-solving skills, ability to work in a fast-paced environment, excellent communication and team collaboration.
• Agile: Experience working in Agile/Scrum methodologies.
