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.