As a Senior Site Reliability Engineer based in Delft, Netherlands, you will own the reliability of TOPdesk's Azure SaaS estate used by thousands of organizations. You will define service-level objectives (SLOs) and error budgets, automate toil, and design the platform to recover itself with minimal manual intervention. You will collaborate with cloud engineering and product squads to ship changes quickly while maintaining resilience, and you will bring AI-native reliability practices to detection, diagnosis, and remediation. What you'll own:

Define and own SLOs and error budgets across the Azure estate (and potential multi-cloud) and use error budgets to balance shipping changes with reliability.
Eliminate toil and build self-healing automation; implement an agent-based support layer that handles recurring toil and feeds improvements back into reliability.
Standardize observability across datacenters; improve metrics, alerting, and tracing; reduce alert-to-incident ratio.
Lead incidents, conduct blameless postmortems, and turn learnings into durable fixes or automation candidates.
Harden CI/CD and progressive delivery (canaries, safe rollouts, automated rollback) to raise both change velocity and reliability.
Model capacity and cost, forecast infrastructure needs across regions, and guide scaling decisions to stay ahead of demand.
Apply AI-native reliability practices using agents and bounded automation.
Maintain runbooks that link to automation candidates and keep documentation clear.
Engage with product teams early in development to embe

About the role

About The Role

As a Senior Site Reliability Engineer based in Delft, Netherlands, you will own the reliability of TOPdesk's Azure SaaS estate used by thousands of organizations. You will define service-level objectives (SLOs) and error budgets, automate toil, and design the platform to recover itself with minimal manual intervention. You will collaborate with cloud engineering and product squads to ship changes quickly while maintaining resilience, and you will bring AI-native reliability practices to detection, diagnosis, and remediation. What you'll own:

Define and own SLOs and error budgets across the Azure estate (and potential multi-cloud) and use error budgets to balance shipping changes with reliability.
Eliminate toil and build self-healing automation; implement an agent-based support layer that handles recurring toil and feeds improvements back into reliability.
Standardize observability across datacenters; improve metrics, alerting, and tracing; reduce alert-to-incident ratio.
Lead incidents, conduct blameless postmortems, and turn learnings into durable fixes or automation candidates.
Harden CI/CD and progressive delivery (canaries, safe rollouts, automated rollback) to raise both change velocity and reliability.
Model capacity and cost, forecast infrastructure needs across regions, and guide scaling decisions to stay ahead of demand.
Apply AI-native reliability practices using agents and bounded automation.
Maintain runbooks that link to automation candidates and keep documentation clear.
Engage with product teams early in development to embe

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