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

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).