Our Azure SaaS estate supports thousands of organisations with SLA-backed 24/7 availability. As a Senior Site Reliability Engineer, you own the reliability of this estate as an engineering problem — you define SLOs, engineer out toil, and make the platform faster to change while preserving resilience. You will sit in the SaaS infrastructure function, collaborating with cloud engineering and product squads to apply AI-native reliability practices, self-healing automation, observability, approvals, containment, and rollback. What you’ll own:

SLOs and error budgets across the Azure (and potentially multi-cloud) estate; use error budgets to balance shipping changes with reliability.
Toil elimination and self-healing automation; create and feed automation into the reliability roadmap; establish an agent-based support layer for recurring toil.
Observability consolidation: standardise metrics, alerting, and tracing; improve coverage; reduce alert-to-incident ratio.
Incident response and blameless postmortems; lead incidents, perform postmortems, implement durable fixes and automation.
Reliability of releases: Harden CI/CD, canaries, safe rollouts, automated rollback to improve both velocity and reliability.
Capacity and performance: Model capacity, load-test critical paths, keep performance within targets across regions.
AI-native reliability: Integrate agents and bounded automation into detection, diagnosis, and remediation.
Runbooks: ensure every alert links to a runbook a

About The Role

Our Azure SaaS estate supports thousands of organisations with SLA-backed 24/7 availability. As a Senior Site Reliability Engineer, you own the reliability of this estate as an engineering problem — you define SLOs, engineer out toil, and make the platform faster to change while preserving resilience. You will sit in the SaaS infrastructure function, collaborating with cloud engineering and product squads to apply AI-native reliability practices, self-healing automation, observability, approvals, containment, and rollback. What you’ll own:

SLOs and error budgets across the Azure (and potentially multi-cloud) estate; use error budgets to balance shipping changes with reliability.
Toil elimination and self-healing automation; create and feed automation into the reliability roadmap; establish an agent-based support layer for recurring toil.
Observability consolidation: standardise metrics, alerting, and tracing; improve coverage; reduce alert-to-incident ratio.
Incident response and blameless postmortems; lead incidents, perform postmortems, implement durable fixes and automation.
Reliability of releases: Harden CI/CD, canaries, safe rollouts, automated rollback to improve both velocity and reliability.
Capacity and performance: Model capacity, load-test critical paths, keep performance within targets across regions.
AI-native reliability: Integrate agents and bounded automation into detection, diagnosis, and remediation.
Runbooks: ensure every alert links to a runbook a

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