Site Reliability Engineer (TechOps)

The role focuses on improving system reliability and performance through software development, automation and infrastructure operations. The ideal candidate will have a solid software development, automation and infrastructure operations. The ideal candidate will have a solid development background, particularly in C#/.NET, along with experience in Microsoft Azure and Infrastructure as Code. 

You'll play a key role in automating processes, reducing operational risks and ensuring systems remain reliable, resilient and scalable.

1. Software engineering for reliability

• Understand, troubleshoot, and improve C#/.NET application code, with a focus on production behaviour, failure modes, and             supportability.

• Build automation, utilities and reusable engineering patterns that remove toil and improve consistency, recovery, and developer experience.

• Apply modern engineering practices including version control, peer review, testing, secure coding, and maintainable design.

• Engineer and support reliable services on Microsoft Azure using cloud-native capabilities and sound operational practices.

• Contribute to resilient, scalable, and cost-aware cloud designs across application and platform layers.

• Identify cloud reliability risks and implement practical improvements that strengthen service operability and recovery.

• Design, improve and support CI/CD pipelines and deployment automation so releases are repeatable, observable, and safe.

• Create and maintain infrastructure as code using Terraform, Bicep, ARM templates, or comparable tooling.

• Use GitOps principles to manage infrastructure and application configuration through version control and automated deployment.

4. Monitoring, observability, and alerting

• Implement and improve application and infrastructure telemetry using logs, metrics, traces, dashboards, and actionable alerts.

• Use observability data to detect, diagnose, and resolve production issues and identify reliability trends and risks.

• Work with platforms such as Dynatrace, Datadog, New Relic, Splunk, Grafana or equivalent technologies.

5. Production engineering and continuous improvement

• Participate in production troubleshooting and incident response using evidence-led diagnosis and clear technical communication.

• Turn incident learning into engineering actions that improve reliability, resilience, scalability, and performance.

• Define and use service-level indicators and objectives, improve runbooks and operational readiness, and support tested recovery practices.

Qualifications, Experience and Skills

• Strong to intermediate hands-on C#/.NET development experience, including understanding and troubleshooting production application code.

• Practical cloud experience, with Microsoft Azure strongly preferred and weighted more highly.

• Good understanding of CI/CD, deployment automation, and modern software delivery practices.

• Hands-on infrastructure-as-code experience using Terraform, Bicep, ARM templates, or similar tooling.

• Practical monitoring, observability, and alerting experience, with working knowledge of GitOps and production troubleshooting.

• Advantageous but not exclusionary: AKS/Kubernetes, Docker, event-driven architectures, messaging, distributed systems, and  performance engineering.

• Proficiency in using AI-enabled productivity tools, such as Copilot, to improve efficiency, generate insight and support decision-making. Applies critical thinking and sound judgement when interpreting outputs, remains accountable for the quality and accuracy of their work

Reliability & resilience- Services meet agreed reliability objectives, recover predictably, and show fewer repeat failures.

Operational toil- Manual, repetitive work is reduced through safe automation, self-service, and reusable engineering patterns.

Observability - Actionable telemetry, dashboards, and alerts improve detection, diagnosis, and service understanding.

Delivery engineering- Deployment processes are repeatable, version-controlled, and increasingly automated.

Developer experience- Delivery teams adopt practical reliability patterns, runbooks, and cloud engineering standards.

Production readiness- Services have usable operational information, tested recovery practices, and clear production supportability.