Site Reliability Engineer

Accountabilities:: Manage production incidents: Take ownership of incidents affecting production clusters in Azure cloud environments, ensuring timely investigation, resolution, and service restoration. Troubleshoot distributed systems: Diagnose complex infrastructure and application issues, conduct root cause analyses, and implement effective solutions to prevent recurrence. Collaborate across teams: Work closely with R&D and Product teams to resolve software defects, communicate operational challenges, and influence product enhancements that improve long-term reliability. Participate in global operations: Contribute to a 24/7 on-call rotation within an international follow-the-sun support model, ensuring continuous service availability. Develop automation solutions: Design and implement code-driven automation tools, internal platforms, and data workflows using cloud services and AI-assisted development technologies such as Cursor, Codex, and Claude. Improve incident management: Build and maintain services that enhance incident response, reporting, operational visibility, and fleet-wide performance insights. Strengthen observability: Improve monitoring and telemetry systems using tools such as Prometheus, Grafana, and Azure Monitor, while developing AI-driven capabilities for data enrichment, anomaly detection, and automated troubleshooting. Drive continuous reliability improvements: Identify opportunities to optimize incident response processes, automate repetitive tasks, and strengthen the stability and scalability of production systems. Requirements: Education and experience: Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience, with at least 4 years of experience in Site Reliability Engineering, Cloud Operations, or Infrastructure Engineering. Cloud infrastructure expertise: Proven experience troubleshooting large-scale production environments and hands-on knowledge of major cloud platforms, including AWS, Azure, or Google Cloud Platform. Operating systems: Strong knowledge of Linux/Unix systems administration, troubleshooting, and performance optimization. Networking knowledge: Solid understanding of networking fundamentals, particularly TCP/IP protocols. Monitoring and observability: Practical experience with monitoring and logging platforms such as Prometheus, Grafana, ELK, Splunk, and Azure Data Explorer, along with the ability to analyze telemetry data using Kusto Query Language (KQL). Programming and scripting: Strong scripting and programming capabilities in Python and Bash. Familiarity with C# or other programming languages is an advantage. AI-assisted development: Experience using AI-powered development tools to accelerate code generation, improve automation workflows, and build more efficient operational tools. DevOps practices: Familiarity with version control systems and CI/CD platforms, including Git, GitLab, and Azure DevOps. Problem-solving abilities: Excellent analytical, troubleshooting, and problem-solving skills, particularly when working with complex, large-scale distributed systems. Automation expertise: Demonstrated ability to design and implement scalable, maintainable automation solutions suitable for production environments. Database knowledge: Familiarity with Redis or other NoSQL database technologies is a plus. Infrastructure as Code: Experience with tools such as Terraform or Pulumi is desirable. Additional qualifications: Relevant cloud or Linux certifications, experience with C#, and exposure to regulated cloud environments, including Sovereign Cloud, are considered advantages. Soft skills: Strong attention to detail, adaptability, curiosity, and a collaborative mindset, with the ability to work effectively in a global, fast-paced engineering environment. Benefits: Remote flexibility: Fully remote working arrangement, offering flexibility in your work location. Global collaboration: The opportunity to work with international engineering teams on large-scale, mission-critical cloud infrastructure. Technical development: Hands-on exposure to advanced cloud technologies, distributed systems, modern SRE practices, and AI-powered operational tools. Innovation-driven environment: Opportunities to contribute ideas, influence product improvements, and build solutions that enhance platform reliability. Inclusive workplace: A diverse and supportive environment that values different perspectives, encourages curiosity, and celebrates individuality. Equal opportunities: A commitment to fair employment practices and an inclusive recruitment process. Accessibility support: Reasonable accommodations are available to candidates who require assistance during the recruitment process.