AI Context Operations Lead

About this role

Headquarters: San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States Mercury is building a whole stack of financial tools for startups. We work hard to create dashboards with thought and simplicity. You can check out our demo dashboard at www.demo.mercury.com . Behind every product Mercury ships is a fast-growing company: dozens of teams across engineering, product, design, data, and business functions, and hundreds of projects that require alignment across compliance, legal, partnerships, customer support, finance, and leadership. AI Ops builds the systems that keep that organization moving, helping teams move quickly without losing shared context. In this role, you'll own Mercury's internal knowledge infrastructure: the systems and standards that make company information accurate, discoverable, and useful. You'll build and maintain a trusted context layer—a structured, living record of what teams own, are building, and know—and ensure it stays current automatically. That context layer powers leadership reporting, planning, operational reviews, and the internal AI agents employees use every day. You'll define how information is organized, validated, and maintained across systems like Linear and Mercury's internal platforms so they function as a single source of truth. Working closely with Engineering, who own the underlying infrastructure, you'll design the knowledge layer above it: the taxonomies, schemas, validation workflows, and automations that make company knowledge reliable for both people and AI systems. This role sits at the intersection of systems operations, knowledge architecture, and product thinking. Success isn't measured by collecting more information, but by creating a high-signal knowledge system that helps employees find answers quickly, enables leaders to make decisions from shared context, and gives AI systems the foundation they need to operate effectively. Mercury aims to make banking* feel secure, reliable, t

Skills

• Product
• Operations