AI/ML Engineer

Overview This role focuses on developing GenAI/LLM solutions such as Chatbots, AI Agents, and Copilots, as well as building RAG systems and integrating LLMs with existing platforms. The role also involves designing production-ready GenAI architectures and deploying AI solutions on cloud platforms. Responsibilities GenAI / LLM Development - Build GenAI applications based on Large Language Models (LLMs) such as Chatbots, AI Agents, and Copilots. - Design and implement RAG pipelines (document ingestion, chunking, embedding, retrieval, re-ranking). - Perform prompt engineering, including prompt templates, system prompts, and tool calling. - Conduct fine-tuning / instruction tuning (when necessary) or adapter-based tuning (LoRA, PEFT). AI Architecture & Integration - Design GenAI architectures for production environments (API-based, microservice-oriented). - Integrate LLMs with existing systems: Web, Mobile, CRM, ERP, CMS, and Data Platforms. - Work with vector databases (FAISS, Milvus, Pinecone, Weaviate, etc.). Requirements Must-have - From 4 years of experience in AI/ML development or Software Engineers transitioning into AI. - Strong proficiency in Python. - Hands-on experience with LLM / GenAI platforms (OpenAI, Azure OpenAI, Gemini, Claude, open-source LLMs). - Experience building RAG systems. - Solid understanding of tokens, context windows, embeddings, temperature, top-k/top-p. - Experience with REST APIs, JSON, and asynchronous processing. Preferred - Experience with LangChain, LangGraph, LlamaIndex, Dify, or equivalent frameworks. - Experience with vector databases (FAISS, Milvus, Pinecone, etc.). - Experience deploying AI solutions on AWS / Azure / GCP. - Knowledge of Docker and CI/CD. - Experience working on client projects (ITO/consulting). Nice to have - Experience with AI Agents (multi-agent systems, tool-based agents). - Experience fine-tuning open-source LLMs (LLaMA, Mistral, Qwen, etc.). - Knowledge of Knowledge Graphs and Hybrid Search (BM25 + Vector). - Experience with traditional NLP techniques. - Understanding of data privacy and security in AI systems. Benefits - Working in a young and professional environment. - Staying in a friendly and spiritual space (daily tea break, weekly sports time, monthly outdoor activity and annual holiday). - Obtaining guidance and awareness of advanced technologies. - Earning very competitive salary. - Being reviewed to increase salary twice per year. - Receiving social insurance according to Vietnamese Government regulations. - Having opportunity to join Football, Gym, Badminton and Swimming Club. - Working hours: 5 days/week (Monday to Friday).