Technical Product Manager – AI & Knowledge Graph, Up to 110k/mth

Technical Product Manager – AI & Knowledge Graph, Up to 110k/mth

Location:

Hong Kong 

Industry:

Artificial Intelligence / RPA

Contact Name:

Yuki Leung

Date Published:

03-Jun-2026

Summary
You will drive the design and technical roadmap of an advanced Knowledge Graph platform, leading an expert AI team building autonomous, multi-agent pipelines. By transforming massive volumes of chaotic, unstructured documents into a structured, searchable knowledge base, you will directly enable next-generation enterprise applications like GraphRAG and semantic search while shielding the institution from shifting regulatory risks.

Responsibilities
  • Formulate the product strategy and execution roadmap for an automated, agentic pipeline turning unstructured data into structured graph entities.
  • Define actionable features and collaborate with business analysts and AI engineers to author clear user stories.
  • Prioritize platform features and detailed story tickets to accelerate time-to-value for business use-case owners.
  • Run core Agile ceremonies including feature planning, daily stand-ups, backlog grooming, and team retrospectives.
  • Bridge communication gaps as the primary translator between business stakeholders, AI engineers, data scientists, and development teams.
  • Integrate rigorous AI and model governance requirements, establishing guardrails to prevent hallucinations, enforce privacy, and maintain data lineage.
Requirement
  • At least 8 years of professional working experience, with a clear focus on technical product management for AI, ML, or data-intensive systems.
  • Proven track record of running effective Agile workflows and team ceremonies alongside strong conflict-resolution skills.
  • Deep structural understanding of the software development lifecycle (SDLC) and modern product prioritization frameworks.
  • Proficiency with Agile project tracking and documentation ecosystems, specifically Jira and Confluence.
  • Technical familiarity with Large Language Models (LLMs), RAG/GraphRAG architectures, vector databases, and autonomous agent frameworks like AutoGen or LangGraph.
  • Background in Knowledge Graphs (such as Neo4j or Falkor) or semantic data technologies including RDF (Resource Description Framework) and WOL (Web Ontology Language).
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