Position Overview We are seeking a highly skilled Generative AI Engineer (or AI Solution Leader) to join our advanced technology division. The ideal candidate will have hands-on experience in LLM (Large Language Model)-based system development, Retrieval-Augmented Generation (RAG) architectures, and AI conversational agent implementation. This position plays a crucial role in designing, prototyping, and leading the implementation of cutting-edge AI solutions that leverage knowledge graphs, vector databases, and natural language understanding to build intelligent, scalable enterprise systems. 1. Responsibilities Design and Develop Generative AI Systems Build and optimize RAG architectures integrating LLMs with structured/unstructured data sources. Develop knowledge graph-based information retrieval systems and implement vector search solutions (e.g., FAISS, Milvus, Pinecone, VertexAI Vector Search). Research & Architecture Research state-of-the-art models (e.g., GPT, Claude, Gemini, Llama) and integrate them into enterprise use cases. Define the AI system architecture from data ingestion to inference and evaluation. AI Conversational Agent Development Design and implement intelligent chatbots capable of contextual understanding and domain-specific reasoning. Integrate conversational flows with backend systems and APIs. Project Leadership Collaborate with clients and internal teams to define user requirements and translate them into technical design specifications. Lead a small AI team (2–5 engineers) to execute design, implementation, and testing phases. Ensure technical quality, scalability, and performance of AI-driven applications. Collaboration & Communication Work closely with product managers, data engineers, and backend/frontend teams. Contribute to proposal creation and proof-of-concept (PoC) activities for client projects. 2. Job Qualifications Core Skills Hands-on experience with LLMs and RAG system design. Proficiency in Python and frameworks such as LangChain, LlamaIndex, Transformers (Hugging Face), or VertexAI SDK. Experience with vector databases (e.g., Pinecone, Weaviate, Milvus, Chroma). Understanding of knowledge graph design and semantic search. Experience building AI chatbots or conversational systems (Dialogflow, Rasa, custom LLM pipelines). Preferred Experience Familiarity with cloud AI platforms (Google VertexAI, Azure OpenAI, AWS Bedrock). Experience with MLOps, prompt engineering, or model fine-tuning. Practical experience deploying LLM applications in production environments. Soft Skills Strong analytical thinking and research capability. Ability to design and lead technical projects independently. 3. Working time 8:00 AM – 12:00 PM | 1:00 PM – 5:00 PM 4. Benefits Compensation & Well-being: Probation: insurance covered 13th-month salary Performance & Salary review twice per year 19 days of paid time off per year Premium healthcare insurance for yourself and family members  Annual health check-ups. Career Development: Sponsored certificates English course Career roadmap and growth opportunities Dynamic working environment: Free snacks in the pantry Happy hour, Party celebration, Team building, Company trip,... Diversified activities: Football, Badminton,... Hybrid working model Kozocom’s environment: a happy, equal, and open-minded environment.