Sr Business Effectiveness Manager, AI

Cribl

8d•$175,000 - $225,000•Remote

About The Position

Cribl is seeking a Senior Business Effectiveness Manager, AI to help a 1,000+ person, remote-first company maximize its AI investments. The role leads the company’s approach to business-critical knowledge and to identifying, developing, and scaling AI use cases and solutions. Working with the Sr. Manager, Business Effectiveness and leaders across functions, this person will turn existing AI activity into shared, reusable infrastructure that improves how teams work. The role establishes and governs a company-wide knowledge strategy, ensuring critical information is accurate, discoverable, and used by AI tools. It also identifies priority AI use cases, helps build universal solutions, and scales successful solutions into company-wide infrastructure. The manager supports AI platform rollouts, mobilizes employees through an AI Champions Network, and tracks adoption, spending, and return on investment in partnership with Finance and Engineering. Cribl is a remote-first company building telemetry infrastructure for the AI era. The salary range for this role is $175,000–$225,000 USD, based on location and job-related knowledge, skills, and experience. Employees in this role are eligible for the Cribl Corporate Bonus Program and a benefits package that includes health, dental, vision, short-term disability, and life insurance; paid holidays and paid time off; a fertility treatment benefit; 401(k); and equity.

Requirements

10+ years of experience in operations, strategy, or knowledge management roles, ideally at a technology company.
Track record of setting strategy and delivering it.
Experience building programs, processes, and governance that turn fragmented cross-functional work into scalable infrastructure.
Strong understanding of knowledge architecture, including how information should be structured, connected, and governed to remain accurate and build on itself.
Hands-on AI fluency, including building agents and workflows, with sufficient technical depth to partner with Engineering, Data, and IT.
Proven ability to drive company-wide adoption without direct authority.
Experience building and running champion or community networks.
Experience defining adoption and impact metrics and using data to guide decisions and priorities.
Strong executive presence and ability to develop business cases that gain buy-in from VP and C-suite stakeholders across competing priorities.
Comfort operating in ambiguity where established playbooks do not exist.
Experience working with remote or distributed teams.

Nice To Haves

Experience with enterprise search platforms such as Glean.
Experience managing or mentoring a team; preferred but not required.

Responsibilities

Set the company’s knowledge strategy with function owners, identify business-critical knowledge, and design a single source of truth.
Maintain the accuracy and currency of business-critical knowledge through regular verification cycles and accountability for content owners.
Partner with AI tool owners to ensure AI tools prioritize business-critical knowledge.
Map context layers across the business and develop a strategy for connecting them, partnering with Data, IT, and Engineering.
Identify and prioritize top AI use cases, make them easy to find and reuse, and lead development of universal solutions where needed.
Track AI solutions being developed across the company and scale high-value solutions into company-wide infrastructure.
Establish processes and verification standards for a shared skills and agents registry.
Monitor developments in AI models, tools, and agentic workflows and translate relevant capabilities into the company’s approach.
Partner on rollouts of company-wide AI platforms and ensure they connect to company knowledge and existing solutions.
Mobilize business experts to drive AI activation at scale, including running the AI Champions Network.
Track company-wide AI adoption, spending, and ROI with Finance and Engineering, providing leaders visibility into results.