For More Open Positions Visit us at:
http://recruiting.woongjininc.com/

Our Mission

WOONGJIN INC. is a rapidly growing team who provides a range of unique, exceptional, and enhanced services to our clients.  We have a strong moral code that includes the service of goodness without expectations of reward.  We are motivated by the sense of responsibility and servant leadership.

We're seeking a skilled engineer to lead the development of cutting-edge RAG applications using state-of-the-art LLM technologies. The ideal candidate will have a strong background in AI and NLP, with hands-on experience in building and optimizing LLM-based systems. This role requires expertise in integrating LLM solutions via APIs with both third-party tools and in-house applications. Experience with AWS Bedrock is highly valued, and familiarity with microservices architecture in cloud environments is a significant plus.

Primary Responsibilities:

• Design and implement RAG (Retrieval-Augmented Generation) systems
• Integrate and optimize Large Language Models (LLMs) via APIs
• Develop efficient information retrieval and extraction systems
• Build and manage databases and vector stores
• Apply Natural Language Processing (NLP) techniques
• Monitor performance and continuously improve systems
• Integrate LLM solutions with other third-party tools and in-house applications
• Design and implement APIs for seamless integration of LLM capabilities

Salary: 100K-110K a year

Requirements:

• Bachelor's degree or higher in Computer Science, Artificial Intelligence, or related field (Master's preferred)
• Proficiency in Python programming
• Deep understanding of LLMs, RAG systems, and API integration
• Experience with NLP and machine learning
• Strong skills in database and API development
• Knowledge of distributed systems and cloud computing
• Expertise in integrating AI models with various software solutions

   

Preferred Qualifications:

• Contributions to open-source LLM projects
• Experience building AI systems in large-scale production environments
• Experience with vector databases (e.g., Pinecone, Faiss)
• Proficiency with relevant libraries such as Transformers, Hugging Face
• Experience with AWS Bedrock for AI/ML model deployment and management
• Experience with microservices architecture (MSA) in cloud environments
• Familiarity with LLM API providers (e.g., OpenAI, Anthropic, Cohere)

All your information will be kept confidential according to EEO guidelines.

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