AI Data Engineer - RAG & Vector DB Architect

Private Advertiser; Hong Kong; On-site; HKD 450,000 - 750,000; Full time

Job summary

Private Advertiser is seeking an experienced AI Data Engineer to design, build, and manage enterprise-grade data architecture and AI knowledge management infrastructure (Retrieval-Augmented Generation / RAG).

You will resolve data fragmentation by creating automated, scalable pipelines across a diversified portfolio, transforming unstructured assets into AI-ready knowledge bases with strong security for downstream AI systems.

Qualifications

• Minimum 3–5 years in Data Engineering or AI data pipeline development in an enterprise environment.
• Advanced proficiency in Python and data manipulation frameworks.
• Hands-on experience with unstructured data parsing libraries.
• Proven implementation experience with Vector Databases and LLM orchestration frameworks (LangChain, LlamaIndex).
• Strong expertise in SQL/NoSQL database management, RESTful API architecture, and enterprise integration patterns.
• Exceptional analytical rigor and structured problem-solving capability for data quality governance.
• Prior experience in Real Estate, Entertainment, or Retail sectors.

Responsibilities

• Architect and maintain robust ETL/ELT pipelines integrating cloud storage, local servers, and legacy enterprise systems.
• Automate extraction, parsing, and normalization of unstructured documents into structured formats for LLM ingestion.
• Deploy and optimize enterprise vector database environments.
• Implement indexing, semantic chunking, and metadata taxonomy strategies to maximize retrieval accuracy and efficiency.
• Enforce RBAC and enterprise data security protocols within the AI retrieval layer.
• Establish automated synchronization routines to monitor data repositories and update vector indices in real time.

Skills

Python

Data pipelines

ETL/ELT

SQL/NoSQL

Tools

LangChain

LlamaIndex

Vector Databases

RESTful APIs

Job description

Private Advertiser is seeking an experienced AI Data Engineer to design, build, and manage enterprise-grade data architecture and AI knowledge management infrastructure (Retrieval-Augmented Generation / RAG).

You will resolve data fragmentation by creating automated, scalable pipelines across a diversified portfolio, transforming unstructured assets into AI-ready knowledge bases with strong security for downstream AI systems.