AI Context Operations Lead

Mercury•3h ago

CanadaRemoteCA$154.1K–CA$192.6KFull-timeMid Level5+ yrs exp

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Operations AnalystOperations ManagerOperations Consultant

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
hundreds of projects that require alignment across compliance, legal, partnerships, customer support, finance
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
useful. You'll build and maintain a trusted context layer—a structured, living record of what teams own, are building
know—and ensure it stays current automatically. That context layer powers leadership reporting, planning, operational reviews
the internal AI agents employees use every day. You'll define how information is organized, validated
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
automations that make company knowledge reliable for both people and AI systems. This role sits at the intersection of systems operations, knowledge architecture
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
gives AI systems the foundation they need to operate effectively. Mercury aims to make banking* feel secure, reliable, thoughtful
perhaps even magical. Your job is to make the company's internal knowledge systems just as dependable.
Mercury is a fintech company, not an FDIC-insured bank. Banking services provided through Choice Financial Group and Column N.A., Members FDIC. You will: Own Mercury's knowledge infrastructure: the trusted context layer that captures what every team owns, is building
knows, along with the information architecture, taxonomy
governance that keep it accurate, current
useful. Build the knowledge layer on top of Mercury's AI infrastructure by partnering with AI Engineering to design the schemas, automations
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
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
other teams to replace fragmented documentation with trusted, structured sources of truth. Continuously improve how Mercury captures, organizes
uses knowledge by identifying operational friction, building better workflows
ensuring employees have the tooling and enablement they need to effectively work with AI. You should: Have 5–8 years of experience in program or product operations, technical program management, product management, data
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
tools like Linear, GitHub, Metabase
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
other practical applications, along with a solid understanding of how LLMs retrieve and consume information. Influence organizations through strong judgment, clear communication
thoughtful execution, thriving in ambiguous environments where the right systems have to be invented rather than inherited. The total rewards package at Mercury includes base salary, equity (stock options)
benefits. Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry. New hire offers are made based on a candidate's experience, expertise, geographic location
internal pay equity relative to peers. Our target new hire base salary ranges for this role are the following: US employees in New York City, Los Angeles, Seattle
the San Francisco Bay Area: $163,000 - $203,800 US employees outside of the New York City, Los Angeles, Seattle
the San Francisco Bay Area: $146,700 - $183,400 Canadian employees (any location): CAD $154,100 - $192,600 *Mercury is a fintech company, not an FDIC-insured bank . Banking services provided through Choice Financial Group and Column N.A., Members FDIC. Mercury values diversity & belonging and is proud to be an Equal Employment Opportunity employer. All individuals seeking employment at Mercury are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation
any other legally protected characteristic. We are committed to providing reasonable accommodations throughout the recruitment process for applicants with disabilities or special needs. If you need assistance
an accommodation, please let your recruiter know once you are contacted about a role. We use Covey as part of our hiring and / or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. [Please see the independent bias audit report covering our use of Covey for more information.] #LI-JD1

Required skills

AIAPIsdata modelsanalyticsLinearGitHubMetabase