Senior Product Manager, Knowledge Graph & AI Platform

PassFort; Greater London; On-site; GBP 120,000 - 160,000; Full time

Job summary

Moody's in London leads enterprise Knowledge Graph initiatives, uniting data and engineering to power analytics, search, and GenAI apps. You will own the Knowledge Graph product roadmap and work with data, platform, and application teams to deliver value.

The role emphasizes translating complex regulatory and data-domain problems into precise requirements, evaluating graph technologies, and driving buy/build decisions to advance risk insights capabilities.

Qualifications

• Experience with sanctions, AML, fraud or related regulatory domains.
• Ability to translate ambiguous business problems into engineering requirements.
• Familiarity with data, platform or AI/ML products preferred.

Responsibilities

• Lead the enterprise Knowledge Graph product management to power analytics, search, and GenAI.
• Evaluate Knowledge Graph technologies and drive build-vs-buy decisions.
• Source and prioritize use cases with clear value hypotheses and success metrics.
• Translate ontology scope, data sources, latency targets, access controls, and integrations.
• Own the product roadmap and run agile ceremonies across multiple teams.
• Communicate progress and risks to both technical and non-technical audiences.
• Define onboarding paths and drive platform adoption.

Skills

Sanctions & AML

AI/ML product mgmt

Data modeling

Graph data modeling

Stakeholder mgmt

Agile / Scrum

Vector databases

Retrieval augmented generation

AI governance

Problem translation

Education

Bachelor's degree (relevant field)

Equivalent practical experience

Tools

Knowledge Graph platforms

Job description

Moody's in London leads enterprise Knowledge Graph initiatives, uniting data and engineering to power analytics, search, and GenAI apps. You will own the Knowledge Graph product roadmap and work with data, platform, and application teams to deliver value.

The role emphasizes translating complex regulatory and data-domain problems into precise requirements, evaluating graph technologies, and driving buy/build decisions to advance risk insights capabilities.