Senior Staff Cloud Backend Engineer - Observability and Site Reliability

As a Senior Staff Data Centre Observability and Site Reliability Engineer, you will design, build, and operate scalable observability and reliability solutions for large-scale datacenter infrastructure. This role focuses on developing high-performance monitoring and telemetry platforms, ensuring system reliability, and driving operational excellence through automation, performance optimization, and SRE best practices. The ideal candidate will work across the full service lifecycle—design, deployment, and continuous improvement—while collaborating with cross-functional teams to enhance visibility, resilience, and efficiency of critical systems.

• Design, implement, and maintain observability solutions for datacenter infrastructure, including monitoring, logging, alerting, and telemetry systems.
• Develop, deploy, and operate large-scale observability and telemetry platforms with a focus on real-time monitoring, high performance, and scalability.
• Own and contribute to the full lifecycle of observability services—from design and development to deployment and ongoing optimization.
• Build and enhance monitoring systems to ensure high availability, reliability, and performance of infrastructure.
• Create and manage dashboards, alerts, and reports to provide clear visibility into system health, performance, and capacity trends.

• Apply SRE principles and best practices to improve reliability, scalability, and operational efficiency of datacenter services.
• Develop and maintain automation for infrastructure provisioning, monitoring, and system management.
• Lead root cause analysis (RCA) and post-incident reviews, driving corrective actions to prevent recurrence and improve system resilience.

• Analyze system and application performance across the datacenter infrastructure to identify bottlenecks and improvement areas.
• Implement optimization strategies to enhance performance, efficiency, and resource utilization.

• Partner with cross-functional engineering teams to understand observability and reliability requirements and deliver effective solutions.
• Collaborate with hardware and software vendors to evaluate, integrate, and optimize new technologies within the ecosystem.

• Ensure observability and reliability solutions adhere to organizational security policies and industry standards.
• Implement and maintain appropriate security controls to safeguard infrastructure, systems, and data.

• Provide hands-on support for observability and reliability issues, including debugging complex hardware and software problems.
• Develop and maintain documentation, including troubleshooting guides and operational best practices, to support efficient issue resolution.

• Stay current with emerging trends, tools, and technologies in observability and SRE, and incorporate them into the platform.
• Continuously enhance the scalability, reliability, and operational efficiency of datacenter services through proactive improvements.

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field. 

• 12+ years of progressive software engineering experience, with a heavy emphasis on distributed systems, cloud-native architectures, or platform operations. 

• Proven experience in managing and optimizing large-scale datacenter environments

• Strong proficiency in Go or Python, with a deep understanding of networked systems and performance optimization. 

• Expert-level knowledge of Kubernetes internals (scheduling, controllers) and containerization ecosystems. 

• Proven experience with load balancing, service mesh, and request routing at scale. 

• Proficiency in observability tools and technologies (e.g., Prometheus, Grafana, ELK Stack).

• Experience with SRE practices and tools (e.g., Kubernetes, Docker, Terraform).

• Familiarity with cloud platforms (AWS, Azure, GCP) and their observability and reliability services

• Prior experience building infrastructure specifically for LLM inference or large-scale training clusters. 

• Familiarity with inference, including mixed precision, kernel tuning, or custom hardware accelerators. 

• Experience managing hybrid-cloud or multi-AZ deployments across AWS, Azure, or GCP. 

• Experience operating in regulated environments with strict security and compliance requirements

• Hybrid
  Our Hybrid work model: Coupang hybrid work model is designed to enable a culture of collaboration that acts a catalyst to enrich the experience of employees. Employees are required to work at least 3 days in the office per week, with the flexibility to work from home 2 days a week, depending on the role requirement. Some businesses may require more time in office due to nature of work.  
  
  

Details to consider 

• Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws. 
   

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