Product Operations Specialist, Jobber

• 1-2 years in Product Operations, Data Operations, QA, DevOps, or a similar where tooling and workflow optimization were part of your role
• Understanding of product management workflows, cross‑functional coordination, and stakeholder engagement
• Working knowledge of automation platforms (e.g., n8n), LLMs, and API integrations, able to configure, test, and monitor AI-enabled workflows in collaboration with engineering and product teams
• Basic data literacy: interpret dashboards, spot anomalies, and escalate
• Strong communication skills and attention to detail, with the ability to manage multiple priorities
• Familiarity with Agile/Scrum frameworks and product release cycles
• A proactive, curious mindset, able to seek out resources and solve problems independently

Desirable

• The Product Operations team at Jobber supports the R&D organization by improving how we work. We streamline processes, manage product tooling, and enhance cross‑functional alignment to help product teams deliver value to customers faster.
• Our role is to remove friction, increase clarity, and provide the operational foundation that allows Product Managers, Designers, and Engineers to focus on building great products
• As a Product Operations Specialist - Automation at Jobber, you’ll help R&D deliver value to customers faster by optimizing workflows, managing tooling, and configuring AI‑enabled automation.
• This role focuses on execution and coordination, helping R&D teams work more effectively, with opportunities to influence how Product Ops scales.
• You won’t be expected to build production systems, but you’ll partner with Engineering when heavier technical lifts are needed. You will work closely with members of R&D, leadership, and cross‑functional stakeholders to ensure smooth operations, effective tool usage, and well‑governed AI capabilities
• Collaborate with Product teams to identify process gaps and and design workflow improvements, using automation platforms where possible
• Promote asynchronous collaboration by maintaining clear documentation, training resources, and templates
• Support the R&D tech stack by tracking tool usage and performance and communicating tooling changes to relevant teams
• Research and assess third-party AI/ML tools, APIs, and platforms for fit and usability, with an eye to adoption in day-to-day Product Ops workflows
• Use AI tools and automation platforms to prototype and configure internal workflows that reduce manual effort and eliminate duplication
• Track AI tool adoption and performance across R&D, maintaining an up-to-date inventory of tools and use cases to support continuous improvement. At Jobber we use AI tools to complement human skills and augment productivity, not to replace human creativity, critical thinking, and decision-making