Incident Operations Specialist

Responsibilities

• Own incident tooling operations: Maintain reliability and configuration of incident.io, PagerDuty, Slack-based workflows, on-call rotations, and escalation paths. Monitor integrations and automations; fix issues.
• Build and maintain AI-powered workflows: Design and ship repeatable automation for incident thread summarization, postmortem draft generation, follow-up triage, severity classification, and data hygiene. Turn experiments into durable systems.
• Build and sustain the IC community: Grow community of practice for Incident Commanders and Support Leads. Run touchpoints, share learnings, coach responders.
• Operate data and reporting systems: Build, maintain, troubleshoot dashboards and reports (Databricks, Grafana, Looker). Ensure data quality, surface trends.
• Maintain documentation and enablement assets: Keep playbooks, templates, incident guides current. Flag gaps.
• Drive continuous improvement: Participate in incidents and postmortems. Identify patterns, implement improvements, surface friction with solutions.
• Partner across the org: Coordinate with Engineering, Support, GTM, Legal, Finance on incidents.
• Support the incident program at scale: Onboard new stakeholder groups, build self-sufficient infrastructure.

Requirements

• Experience in incident response, technical operations, or reliability-adjacent role.
• Hands-on familiarity with incident tooling (incident.io, PagerDuty or equivalent) and Slack-based workflow automation.
• Comfortable with SQL and reporting tools (Databricks, Looker, Grafana).
• Able to diagnose issues using logs, system context, integration debugging.
• Can build lightweight automations, configure APIs, prototype AI workflows.
• Demonstrable daily AI usage for drafting, summarizing, building workflows, triaging.
• Built repeatable AI-powered workflows (beyond one-off prompts).
• Applies verification/judgment to AI outputs in high-pressure contexts.
• Can articulate AI impact on speed, quality, or capacity.
• Independently drives problems to resolution.
• Strong attention to detail in configuration, data quality, documentation.
• Works visibly with proactive updates.
• Proven track record of respectfully disagreeing and committing.

Nice-to-Haves

• Experience with observability tools (Datadog, Grafana, Prometheus, Opensearch, Graylog).
• Comfortable in GitLab, Coda, Slack APIs.
• Empathy for commanders under pressure; gives constructive feedback.
• Async-first communication; writes clearly and proactively.
• Prioritizes ruthlessly and escalates trade-offs.

Compensation

• Base salary range: $108,200 - $178,500 (varies by location, experience, and skills).