Remote Senior AI & Automation Lead – Customer Support

Jobgether

Canada

On-site

CAD 115,000 - 160,000

Full time

4 days ago

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Benefits offered by this job

Remote-first with distributed teams

Comprehensive benefits package

Career development and growth

Opportunity to shape AI strategy

Global customer impact

Job summary

Jobgether seeks a Sr Lead, AI & Automation - Customer Support based in Canada to lead the design, deployment, and governance of AI-powered support tools. You will own the knowledge base, build automation workflows, and partner with AI, Product, and Support teams to reduce repetitive work while improving accuracy and customer satisfaction.

The role blends hands-on technical work with team leadership in a fast-growing SaaS environment.

Qualifications

5+ years of experience in AI and automation implementation, support enablement, knowledge management, or a related field.
Hands-on experience with AI agents, LLMs, automation workflows, or similar technologies, with the ability to build solutions.
Demonstrated experience mentoring, managing, or leading individuals or small teams, formally or informally.
Strong systems-thinking capabilities, with the ability to identify operational friction and design solutions around complete workflows.
Experience owning customer self-service, support content, knowledge management, or related programs, ideally with accountability for both answer quality and insights generated from customer questions.
Strong cross-functional collaboration skills, with the ability to work effectively with technical AI teams, support specialists, product teams, and business stakeholders.

Responsibilities

Design, build, and deploy AI agents and automation workflows that address friction points across customer support operations, owning architecture and implementation.
Translate opportunities into a prioritized AI and automation roadmap by identifying repetitive tasks and slow processes.
Monitor and improve AI quality and performance in production, including accuracy, tone, and escalation rates.
Stay current with LLMs, agent frameworks, and semantic search to identify practical applications.
Lead a small team of knowledge and AI enablement specialists and develop their capabilities.
Own the knowledge base and internal documentation ecosystem, ensuring accuracy and governance.
Establish content, taxonomy, and knowledge-management practices to improve discoverability and agent performance.
Own end-to-end self-service experiences across guides and AI-powered answers, ensuring high accuracy and relevant responses.