Incident Operations Specialist

As Zapier expands into the enterprise market, incident management is a front-line function for customer trust and operational reliability. The Incident Operations Specialist is the engine that keeps the day-to-day operation of Zapier's incident program running: reliably, visibly, and at scale. Reporting to the Incident Program Manager, you own the execution of the systems, workflows, and tooling that power incident response across the company. This is not a pure engineering role; it is an ops role with technical depth, for someone who thinks in systems, writes automation to scale their own work, and leaves things more reliable than they found them.

Responsibilities

• Own incident tooling operations: maintain the reliability and configuration of incident.io, PagerDuty, Slack-based workflows, on-call rotations, and escalation paths, and fix what breaks.
• Build and maintain AI-powered workflows: incident thread summarization, postmortem draft generation, follow-up triage, severity classification, and data hygiene, turning one-off experiments into durable systems.
• Build and sustain a community of practice for Incident Commanders and Support Leads, running regular touchpoints and coaching responders on what good looks like.
• Operate data and reporting systems: build and troubleshoot dashboards and reports in Databricks, Grafana, and Looker, ensuring data quality and metric accuracy.
• Keep playbooks, templates, and incident guides current and usable under pressure.
• Participate in incidents and postmortem reviews, identify patterns, and surface recurring friction with recommended solutions.
• Coordinate across Engineering, Support, GTM, Legal, and Finance, and help onboard new stakeholder groups as the program expands.

Qualifications

• Experience in incident response, technical operations, or a reliability-adjacent role, with hands-on familiarity with incident tooling and Slack workflow automation.
• Comfortable building with SQL and reporting tools (Databricks, Looker, Grafana), and able to diagnose operational issues using logs and integration debugging.
• Able to build lightweight automations, configure API integrations, and prototype AI agents without needing an engineer to do it for you.
• Demonstrable daily AI fluency: repeatable AI-powered workflows with verification and judgment built in, and a clear account of how they changed throughput or quality.
• Strong attention to detail in configuration, data quality, and documentation, with visible, async-first working habits.
• Clear written communication across engineering, support, and leadership audiences, including translating technical incident detail for non-technical partners.