AI Context Operations Lead

Embedded Shishya; San Francisco, New York, Portland (CA, NY, OR); Hybrid; USD 163,000 - 203,800; Full time

Benefits offered by this job

Equity (stock options)

Competitive benefits

Job summary

Mercury is seeking a leader to own and evolve our internal knowledge infrastructure, defining the taxonomies, schemas, validation workflows, and governance that keep company information accurate, discoverable, and useful. You’ll collaborate with AI Engineering to build a trusted context layer over Mercury’s AI platform, enabling leadership reporting and strategic decision-making.

You should have 5–8 years in program/product operations or related roles, with a systems design mindset and hands-on

Qualifications

• 5–8 years of experience in program or product operations or similar roles.
• Ability to turn messy information into scalable structures.
• Experience with APIs, data models, analytics.
• Hands-on with AI-driven workflows and automation.
• Strong judgment and communication in ambiguous environments.

Responsibilities

• Own Mercury’s knowledge infrastructure and governance.
• Design schemas, automations, and validation workflows.
• Develop leadership reporting and strategic roadmaps.
• Partner with cross-functional teams to standardize systems.
• Ensure knowledge remains current and trusted.

Skills

Systems design

Knowledge architecture

APIs and data models

AI workflows

Cross-functional collaboration

Clear communication

Tools

Linear

GitHub

Metabase

AI platforms

Job description

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, thoughtful, and 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, 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.

You should:

• Have 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.

Total Rewards Package

The total rewards package at Mercury includes base salary, equity (stock options), and 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, and 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, or the San Francisco Bay Area: $163,000 - $203,800 US employees outside of the New York City, Los Angeles, Seattle, or 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.

Equal Employment Opportunity

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, or 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, or 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.]