Note: The job is a remote job and is open to candidates in USA. Mercury is building a whole stack of financial tools for startups. In this role, you'll own Mercury's internal knowledge infrastructure and design systems that ensure company information is accurate, discoverable, and useful.
Responsibilities
- Own Mercury's knowledge infrastructure: the trusted context layer that captures what every team owns, is building, and knows, along with the information architecture, taxonomy, and governance that keep it accurate, current, and useful
- Build the knowledge layer on top of Mercury's AI infrastructure by partnering with AI Engineering to design the schemas, automations, and validation workflows that allow people and AI agents to reliably retrieve and act on company knowledge
- Own the reporting layer that turns shared context into operational insight, including leadership reporting, roadmap views, planning dashboards, and the reporting that powers company operating cadences
- Drive company-wide adoption of standardized systems and practices by partnering across Engineering, Product, Design, Data, Compliance, Legal, Finance, Partnerships, Customer Support, and other teams to replace fragmented documentation with trusted, structured sources of truth
- Continuously improve how Mercury captures, organizes, and uses knowledge by identifying operational friction, building better workflows, and ensuring employees have the tooling and enablement they need to effectively work with AI
Skills
- 5–8 years of experience in program or product operations, technical program management, product management, data, or similar roles where you drove company-wide systems or operational improvements
- Think like a systems designer and knowledge architect, able to turn messy, distributed information into simple, scalable structures that people and AI systems can easily understand and trust
- Be comfortable working with technical systems, including APIs, data models, analytics, and tools like Linear, GitHub, Metabase, and modern AI platforms, even if you aren't building the underlying infrastructure yourself
- Have hands-on experience using AI to create leverage through workflows, automations, agents, or other practical applications, along with a solid understanding of how LLMs retrieve and consume information
- Influence organizations through strong judgment, clear communication, and thoughtful execution, thriving in ambiguous environments where the right systems have to be invented rather than inherited
Company Overview
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