Jr. AI Developer - Korean Bilingual MUST

∙ Design, develop, and maintain Generative AI applications using Python and modern AI frameworks.

∙ Develop AI-powered enterprise solutions leveraging Large Language Models (LLMs), including OpenAI, Azure OpenAI, Amazon Bedrock, or similar AI platforms.

∙ Build Retrieval-Augmented Generation (RAG) solutions using enterprise data sources, vector databases, embeddings, and knowledge retrieval techniques.

∙ Design and develop Agentic AI workflows that enable autonomous task execution, reasoning, planning, and tool utilization.

∙ Develop AI agents using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or similar agent orchestration technologies.

∙ Perform prompt engineering and optimize LLM responses for accuracy, reliability, and business use cases.

∙ Integrate Generative AI capabilities into existing enterprise applications through REST APIs and backend services.

∙ Develop AI-powered chatbots, copilots, and intelligent automation solutions.

∙ Support integration of AI models with business systems, databases, and enterprise platforms.

∙ Design and implement API services using Python frameworks such as FastAPI or Flask.

∙ Develop data processing pipelines for AI applications, including data preparation, transformation, and indexing.

∙ Work with relational databases and vector databases to support AI knowledge management solutions.

∙ Support AI model evaluation, testing, monitoring, and continuous improvement.

∙ Assist with deployment and operation of AI applications in cloud environments.

∙ Participate in MLOps/LLMOps activities including CI/CD automation, model lifecycle management, and application monitoring.

∙ Collaborate with application developers, DevOps engineers, and business teams to deliver AI-driven solutions.

∙ Troubleshoot application issues and improve system performance and reliability.

∙ Document AI solutions, architecture, development processes, and operational procedures.

∙ Participate in Agile/Scrum ceremonies, sprint planning, and technical discussions.

∙ Bachelor's degree in Computer Science, Engineering, Data Science, or related field, or equivalent professional experience.

∙ Working knowledge of Python programming language.

∙ Understanding of Generative AI concepts, Large Language Models (LLMs), and AI application development.

∙ Experience or academic/project exposure with LLM-based application development.

∙ Understanding of Retrieval-Augmented Generation (RAG) architecture and AI knowledge retrieval concepts.

∙ Familiarity with prompt engineering techniques and LLM response optimization.

∙ Basic understanding of AI Agent concepts, including workflow automation, reasoning, and tool integration.

∙ Experience with REST API development and integration.

∙ Understanding of database concepts including SQL, data modeling, and data processing.

∙ Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.

∙ Exposure to AI/ML frameworks and libraries such as LangChain, PyTorch, TensorFlow, or similar technologies.

∙ Basic knowledge of software development practices including Git, version control, and code reviews.

∙ Understanding of DevOps concepts including CI/CD pipelines and containerization (Docker preferred).

∙ Experience working with Linux environments.

∙ Strong problem-solving skills and ability to learn emerging technologies quickly.

∙ Excellent verbal and written communication skills.

Performance Expectations

∙ Develop and deploy enterprise Generative AI applications that improve business productivity.

∙ Build reliable AI Agent workflows capable of automating business processes.

∙ Design effective RAG solutions using enterprise knowledge sources.

∙ Improve LLM application accuracy through prompt engineering and evaluation.

∙ Create scalable AI application architectures and reusable AI components.

∙ Collaborate effectively with business users and technical teams to deliver AI solutions.

∙ Continuously learn and apply emerging AI technologies to enterprise use cases.

Preferred Qualifications

∙ Experience developing enterprise Generative AI applications or AI automation solutions.

∙ Hands-on experience with Agentic AI frameworks such as LangGraph, AutoGen, CrewAI, or similar technologies.

∙ Experience with cloud AI services such as:

-Amazon Bedrock

-Azure OpenAI Service

-AWS SageMaker

-Azure AI Studio

∙ Experience with vector databases such as:

-FAISS

-ChromaDB

-Pinecone

-OpenSearch Vector Engine

∙ Experience building AI-powered chatbots, copilots, or intelligent assistants.

∙ Knowledge of Java/Spring Boot enterprise application development.

∙ Experience with enterprise system integration and application operations.

∙ English-Korean bilingual communication skills.

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