Jobber
Senior Manager, Enablement & Knowledge Systems
Edmonton · Senior
Sponsorship not specifiedDetected 121 days ago
LLMsAgentic AIPerformance ManagementOnboardingCustomer SuccessLeadershipCommunicationCollaborationMentoringPublic Speaking
About the role
- This is an AI-first enablement role, with knowledge management at its core.
- You are not simply rolling out tools or creating content; you are designing the knowledge infrastructure, governance, feedback loops, and adoption practices that make AI reliable, useful, and trusted.
- This is a highly autonomous, impact-oriented role-ideal for someone who thrives in ambiguity, can move quickly from strategy to operating rhythm, and brings both systems thinking and hands-on execution.
Responsibilities
- Design programs and rituals that help Customer Success teams find, use, trust, and improve knowledge in the flow of work.
- Drive adoption of KM and AI-enabled workflows through change management, stakeholder engagement, communications, and manager enablement.
- Own the operating model for Knowledge Management across Customer Success - governance, intake, prioritization, ownership, publishing standards, and lifecycle management from capture through continuous improvement.
- Own the structure and quality of Jobber's knowledge ecosystem, including playbooks, SOPs, Help Center content, and AI-facing sources.
- Partner with Product, Support, Onboarding, and Engineering to translate product changes into trusted, actionable knowledge at release pace.
- Ensure knowledge is designed for both human usability and machine readability, including structure, chunkability, metadata, canonical sources, and retrieval performance.
- Own the knowledge layer that powers AI-assisted Customer Success workflows, including agent assist, LLM-based search, AI agents, IVR/voice bot content, and self-service.
- Partner cross-functionally to define AI enablement requirements - content readiness, retrieval quality, governance, permissions, escalation paths, and human-in-the-loop validation.
- Develop AI readiness standards for knowledge assets, including structure, chunkability, metadata, canonical sources, freshness, source traceability, access controls, and retrieval performance.
- Create feedback loops between AI outputs, frontline users, customer outcomes, and knowledge owners so AI systems improve continuously rather than decay over time.
Requirements
- Experience designing or governing AI-enabled workflows where knowledge quality directly impacts AI quality, such as agent assist, AI agents, LLM-based search, self-service, chatbots, voice bots, or workflow automation.
- You have a strong understanding of AI-ready knowledge practices like retrieval quality, content structure, feedback loops, and hallucination risk.
- Experience with knowledge platforms, help centres, content management tools, AI support tools, search analytics, QA/call intelligence inputs, and product release enablement practices.
- Build and maintain the content model, taxonomy, tagging strategy, metadata standards, and source-of-truth practices required to make knowledge findable, reusable, measurable, and AI-ready.
Compensation
- At Jobber, we believe that compensation should be transparent, fair, and reflective of your experience and growth.
- This role has a minimum annual salary of $132,400, a midpoint of $155,700, and a maximum salary of $179,100, designed to show the progression from learning the ropes to truly excelling.
- We design our compensation to reflect each new hire's skills, experience against the complexity of the role, ensuring a fair and competitive salary.
- Our range is intentionally broad to support growth and long-term impact, with fully established hires typically starting around the midpoint.
- The higher end of the range is reserved for those who have demonstrated deep expertise and lasting contributions, while offers below the midpoint reflect strong potential with room to develop.
- This approach ensures that compensation aligns with both an individual's current capabilities and their opportunity for future growth.
Benefits
- Define and report on KM health metrics - quality, freshness, findability, self-service performance, and knowledge gaps - using search analytics, frontline feedback, and AI performance signals to drive priorities.
- Support onboarding and continuous learning by ensuring critical knowledge is accessible, current, role-specific, and embedded where teams need it most.
Company info
- Our Customer Success team works together with other teams and stakeholders to bring our company values to life for our customers.
- By being humble, supportive, and truly giving a sh*t, the team ensures that our customers are successful in Jobber.
- This team thrives on meaningful and impactful communication with one another and with our customers and plays a significant role in the lives of entrepreneurs and business owners who utilize Jobber.
- The Enablement team is a central function within Jobber's Customer Success organization, supporting the growth and performance of Customer Onboarding and Product Support.
- As a Center of Excellence, Enablement owns the programs, tools, and frameworks that drive operational excellence and skill development in these areas.
- We work cross-functionally to ensure that every team member-regardless of channel or customer type-has the knowledge, confidence, and support to deliver value.
- We're looking for a Senior Manager, Enablement & Knowledge Systems to be part of our Customer Success department.
- With Jobber they can quote, schedule, invoice, and collect payments from their customers while providing an easy and professional customer experience.
- Running a small business today isn't like it used to be-the way we consume and deliver service is changing rapidly, technology is evolving, and customers expect more.
- Our culture of transparency, inclusivity, collaboration, and innovation has been recognized by Great Place to Work, Canada's Most Admired Corporate Cultures, and more.
- With an Executive team that has over thirty years of industry experience of leading the way, we've come a long way from our first customer in 2011-but we've just scratched the surface of what we want to accomplish for our customers https://www.youtube.com/watch?v=EkfZmHrRLx4&list=PLoktA_D-2UEnxMLfCe93bANKXVXd2bdN8&index=24.
This listing is sourced directly from Jobber's careers page and normalized into a canonical job model.