Senior AI/ML Engineer

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).