AI Knowledge Ops Lead

Slope; United States; On-site; USD 146,700 - 203,800; Full time

Job summary

Mercury is building a comprehensive internal knowledge system to keep company information accurate, discoverable, and useful. You will own the knowledge infrastructure and the living context layer that defines who owns what, what is being built, and what is known across teams.

Working with Engineering and AI teams, you will design the higher-level schemas, validation workflows, and governance that enable trusted data for people and AI agents, while powering leadership reporting and planning

Qualifications

• 5–8 years in program/product operations or related roles.
• Ability to turn distributed information into scalable structures.
• Experience with APIs, data models, analytics.
• Hands-on AI workflow and automation experience.
• Strong judgment and clear communication in ambiguity.

Responsibilities

• Own Mercury's knowledge infrastructure: the trusted context layer with architecture, taxonomy, governance.
• Collaborate with AI Engineering to design schemas, automations, and validation workflows.
• Own the reporting layer turning context into leadership dashboards and operational insight.
• Promote company-wide adoption of standardized systems across cross-functional teams.
• Continuously improve knowledge capture, workflows, and tooling for AI-enabled work.

Skills

Systems design

Knowledge architecture

APIs

Data models

Analytics

AI workflows

Communication

Tools

Linear

GitHub

Metabase

AI platforms

Job description

Mercury is building a comprehensive internal knowledge system to keep company information accurate, discoverable, and useful. You will own the knowledge infrastructure and the living context layer that defines who owns what, what is being built, and what is known across teams.

Working with Engineering and AI teams, you will design the higher-level schemas, validation workflows, and governance that enable trusted data for people and AI agents, while powering leadership reporting and planning