Systems Reliability Engineer

over 8 years ago

Auckland, New ZealandSenior

Responsibilities

Design cloud deployment architectures on Azure alongside development teams.
Lead provisioning of deployment environments, including servers, services, networking, and communication with technical client stakeholders.
Implement security, scalability, supportability, and performance considerations in solution architectures.
Assist development teams with continuous integration and deployment pipelines and conduct software releases where automation is incomplete.
Configure monitoring and alerting tools and integrate them with support desk software.
Triage and troubleshoot support tickets, diagnose reactive issues, participate in shared after-hours on-call, and complete incident reports.
Implement incident mitigations and proactive continuous improvement programs to reduce recurring support issues.
Automate recurring tasks and document system architecture and deployment processes with AI assistance.
Share technical knowledge with support developers across multiple teams.

Previous experience as a Site Reliability Engineer, Systems Reliability Engineer, DevOps Engineer, or equivalent.
Comfort using AI to diagnose, script, automate, and document work within an AI-assisted delivery pipeline.
Expertise developing scalable web applications.
Some proficiency in Rust, Java, .NET, Go, JavaScript, HTML, CSS, Node.js, ReactJS, AngularJS, or similar front-end frameworks.
Proven scripting experience with PowerShell, Ruby, Python, shell, or other common scripting languages.
Strong experience with Microsoft Azure deployment architectures, Microsoft DevOps deployment pipelines, GitHub Actions, and Terraform.
Experience administering Linux cloud-based server environments and troubleshooting and configuring virtual networks.
Familiarity configuring New Relic, Dynatrace, or similar monitoring frameworks, including dashboards and alerting integrations.
AWS and Bamboo or Bitbucket Pipelines experience is advantageous.
Ability to switch context across technologies and complex environments and remain calm during high-priority issue resolution.
Good judgment when evaluating AI-generated diagnoses and willingness to learn and up-skill.
Must be based in Auckland.

Hybrid working from home and the office, with office attendance required three days per week and occasionally as needed for clients and teams.
Innovative, learning-focused, and collaborative work culture.
Interesting and diverse work for well-respected clients.
Professional growth and development opportunities.
Fortnightly knowledge-sharing sessions with lunch.
Employee Share Purchase Scheme.
Candidates progressing in the process may be asked to complete police background, credit history, or other checks and provide qualification evidence.

51-200 employees