• Respond to live incidents • Receive automated alerts and technical escalations from Support, then establish customer impact, severity, blast radius and the current system state. • Investigate using logs, metrics, traces, dashboards, deployment history, infrastructure, databases, queues, background jobs, APIs and application code. • Use AI throughout triage and diagnosis while checking its conclusions against real evidence. • Choose and execute a proportionate mitigation, rollback, repair or bounded fix. • Validate that the customer outcome has recovered - not only that an alert has cleared or a dashboard has turned green. • Keep ownership, uncertainty, decisions and next actions visible, and give Support clear technical facts for customer communication. • Join customer conversations occasionally when direct technical involvement is genuinely useful. • Bring in the relevant product team when an incident requires deep product knowledge, a material product decision or a substantial root-cause fix. • Escalate with evidence, customer impact, actions already taken and the specific decision or help required. • Protect developers from routine pages; they should normally be disturbed only for genuine P0/P1 impact or product-specific judgement that cannot safely wait. • Produce a clear incident record and handover, and make sure immediate mitigation, product follow-up and reliability-process follow-up reach the right owners. • Remove, consolidate and tune low-value alerts, and design monitoring around real service and customer outcomes. • Analyse material incidents with AI, validate the conclusions and turn repeated failure patterns into better alerts, runbooks, AI Skills, automation or product improvements. • Improve dashboards, diagnostics, service ownership and escalation information so common incidents are easier to understand and resolve. • Create safe, supervised automation for common operational actions. • Work with product teams to close observability, rollback, runbook and supportability gaps. • Detect and help contain unusual service-cost behaviour, then route wider follow-up to the appropriate cost or product owner. • Make reliability and on-call performance easier for the company to understand and improve over time.

• Respond to live incidents • Receive automated alerts and technical escalations from Support, then establish customer impact, severity, blast radius and the current system state. • Investigate using logs, metrics, traces, dashboards, deployment history, infrastructure, databases, queues, background jobs, APIs and application code. • Use AI throughout triage and diagnosis while checking its conclusions against real evidence. • Choose and execute a proportionate mitigation, rollback, repair or bounded fix. • Validate that the customer outcome has recovered - not only that an alert has cleared or a dashboard has turned green. • Keep ownership, uncertainty, decisions and next actions visible, and give Support clear technical facts for customer communication. • Join customer conversations occasionally when direct technical involvement is genuinely useful. • Coordinate the right response • Bring in the relevant product team when an incident requires deep product knowledge, a material product decision or a substantial root-cause fix. • Escalate with evidence, customer impact, actions already taken and the specific decision or help required. • Protect developers from routine pages; they should normally be disturbed only for genuine P0/P1 impact or product-specific judgement that cannot safely wait. • Produce a clear incident record and handover, and make sure immediate mitigation, product follow-up and reliability-process follow-up reach the right owners.

• Respond to live incidents • Maintain accurate incident records and handover • Improve the reliability system • Coordinate the right response • Protect developers from routine pages • Deliver timely and accurate impact assessments • Use AI throughout triage and diagnosis • Produce a clear incident record • Validate that customer outcome has recovered • Keep ownership, uncertainty, decisions and next actions visible

• Respond to live incidents • Receive automated alerts and technical escalations from Support, then establish customer impact, severity, blast radius and the current system state. • Investigate using logs, metrics, traces, dashboards, deployment history, infrastructure, databases, queues, background jobs, APIs and application code. • Use AI throughout triage and diagnosis while checking its conclusions against real evidence. • Choose and execute a proportionate mitigation, rollback, repair or bounded fix. • Validate that the customer outcome has recovered - not only that an alert has cleared or a dashboard has turned green. • Keep ownership, uncertainty, decisions and next actions visible, and give Support clear technical facts for customer communication. • Join customer conversations occasionally when direct technical involvement is genuinely useful. • Bring in the relevant product team when an incident requires deep product knowledge, a material product decision or a substantial root-cause fix. • Escalate with evidence, customer impact, actions already taken and the specific decision or help required. • Protect developers from routine pages; they should normally be disturbed only for genuine P0/P1 impact or product-specific judgement that cannot safely wait. • Produce a clear incident record and handover, and make sure immediate mitigation, product follow-up and reliability-process follow-up reach the right owners. • Remove, consolidate and tune low-value alerts, and design monitoring around real service and customer outcomes. • Analyse material incidents with AI, validate the conclusions and turn repeated failure patterns into better alerts, runbooks, AI Skills, automation or product improvements. • Improve dashboards, diagnostics, service ownership and escalation information so common incidents are easier to understand and resolve. • Create safe, supervised automation for common operational actions. • Work with product teams to close observability, rollback, runbook and supportability gaps.