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Salary
≈ $17k – $42k per year (Estimated)
Location
In office (Ho Chi Minh City)
Seniority
Senior

Confirmed on the employer's own hiring board on Oct 19, 2026. First seen by Alion on Oct 12, 2026.

Overview
Company
Impact
Profile match
VNG Corporation is a major Vietnamese technology company founded in 2004 (originally as VinaGame) that grew to become the country's first tech "unicorn". It operates a vast digital ecosystem encompassing online game publishing, cloud services, and digital media across domestic and international markets. Among its most notable products are Zalo, Vietnam's leading messaging and social application, and ZaloPay, a popular mobile payment platform.
  • Nghiên cứu, thiết kế và tối ưu kiến trúc AI Agent: planning, tool-use / function calling, memory, multi-agent orchestration cho RAGEngine và các sản phẩm AI của GreenNode.
  • Xây dựng và tối ưu pipeline Agentic RAG end-to-end: ingestion, chunking, embedding, hybrid retrieval (dense/sparse), reranking, query rewriting/decomposition, iterative & self-reflective retrieval.
  • Thiết kế hệ thống đánh giá chất lượng agent và RAG: faithfulness, answer relevancy, retrieval precision/recall; xây dựng benchmark và quy trình đánh giá tự động (LLM-as-a-judge, RAGAS hoặc tương đương).
  • Tối ưu đồng thời chất lượng - độ trễ - chi phí: semantic caching, model routing, prompt optimization, context management/compression.
  • Phối hợp với các team sản phẩm và hạ tầng để đưa kết quả nghiên cứu vào production trên nền tảng mô hình self-host của GreenNode.
  • Theo dõi các nghiên cứu và chuẩn mới (agent frameworks, MCP, A2A, deep research patterns...) và đề xuất áp dụng vào sản phẩm.

Yêu cầu

  • Từ 2 năm (Middle) đến 4+ năm (Senior) kinh nghiệm AI/ML Engineering, trong đó tối thiểu 1-2 năm làm việc trực tiếp với ứng dụng LLM.
  • Thành thạo Python; có kinh nghiệm với các framework agent/RAG (LangChain/LangGraph, LlamaIndex, AutoGen, CrewAI...) hoặc tự xây dựng hệ thống agent từ đầu.
  • Hiểu sâu về LLM trong thực tế: prompt engineering, function calling, structured output, quản lý context window.
  • Kinh nghiệm với embedding và vector database (Milvus, Qdrant, Weaviate, pgvector...), kỹ thuật search/IR: BM25, hybrid search, reranker (cross-encoder).
  • Đã đưa hệ thống LLM lên production: thiết kế API, monitoring, observability/tracing (Langfuse, OpenTelemetry hoặc tương đương).
  • Tiếng Anh đọc hiểu tốt tài liệu kỹ thuật và paper.
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