AI Context Operations Lead

About the role

Mercury is building a comprehensive financial platform for startups, focusing on intuitive and well-designed tools. This role is central to ensuring our internal operations are as reliable and thoughtful as our customer-facing products. You will be responsible for the systems that maintain accurate and accessible company knowledge.

Key facts

What you'll do

• Oversee Mercury's internal knowledge systems, including the information architecture, classification, and governance that ensure company data is precise, up-to-date, and valuable.
• Collaborate with AI Engineering to construct the knowledge layer atop our AI infrastructure, defining the data structures, automated processes, and verification methods that enable both employees and AI agents to effectively access and utilize company information.
• Manage the reporting mechanisms that translate collective understanding into actionable insights, supporting leadership reviews, strategic planning, and operational cadences.
• Champion the adoption of consistent systems and practices across all departments, including Engineering, Product, Design, Data, Compliance, Legal, Finance, Partnerships, and Customer Support, to replace scattered documentation with unified, dependable sources of truth.
• Continuously refine how Mercury gathers, structures, and employs knowledge by identifying operational inefficiencies, developing improved workflows, and ensuring employees have the necessary tools and support to work effectively with AI.

Requirements

• Possess 5 to 8 years of experience in program operations, product operations, technical program management, product management, data roles, or similar positions where you have led company-wide system or operational enhancements.
• Demonstrate a capacity for systems design and knowledge architecture, with the ability to transform dispersed and unstructured information into clear, scalable frameworks that are easily understood and trusted by both humans and AI.
• Be proficient in working with technical systems, including APIs, data models, analytics, and tools such as Linear, GitHub, and Metabase, as well as modern AI platforms, even if your primary focus is not on building the core infrastructure.
• Have practical experience applying AI to enhance workflows, automate tasks, develop agents, or in other functional capacities, coupled with a strong grasp of how large language models retrieve and process information.
• Excel at influencing organizational practices through sound judgment, clear communication, and effective execution, particularly in environments with ambiguity where new systems need to be created.

Nice to have

• Experience with knowledge graphs or semantic web technologies.
• Familiarity with internal developer platforms or developer experience initiatives.

Skills & tools

• Linear
• GitHub
• Metabase
• Modern AI platforms
• APIs
• Data modeling
• Analytics

Practical notes

• Total compensation includes base salary, equity (stock options), and benefits.
• Target new hire base salary ranges:
• US employees in New York City, Los Angeles, Seattle, or the San Francisco Bay Area: $163,000 - $203,800
• US employees outside of these major areas: $146,700 - $183,400
• Canadian employees (any location): CAD $154,100 - $192,600
• Mercury is an Equal Employment Opportunity employer and values diversity and inclusion. Reasonable accommodations are available for applicants with disabilities.
• The company uses Covey in its hiring process for certain roles, which may involve providing job requirements and candidate applications to the tool.