Cloud Native SRE Engineer (Contract Role)

Job Responsibilities

1. Global Infrastructure & Business Stability Assurance

Responsible for high availability, stability and performance operation & maintenance of globally distributed infrastructure built on AWS and Tencent Cloud for the company’s core business. Take ownership of core business SLA targets, coordinate end-to-end stability governance of production environments, ensure 7×24 smooth operation of global business, and rapidly mitigate major online incidents and emergent risks. Deeply drive the implementation and routine operation of Kubernetes + Envoy/Istio service mesh architecture, lead the development of traffic governance, link control, permission specification and fault isolation capabilities, and unify O&M standards for the gateway layer.

2. Reliability Metrics & Risk Governance

Lead the design and implementation of SLO/SLI/ErrorBudget reliability metric systems, establish a quantifiable, observable and reviewable stability operation mechanism. Proactively identify bottlenecks in distributed system architecture, single points of failure and disaster recovery gaps, and lead special initiatives including architecture refactoring, disaster recovery enhancement and high-availability transformation to eliminate stability hazards at the architectural level. Lead full-cycle post-incident reviews for online outages, deliver root cause analysis and closed-loop improvement plans, promote R&D teams to implement change control, risk prediction and emergency response mechanisms, and roll out standardized SRE reliability engineering practices.

3. O&M Automation & SRE Efficiency Platform Construction

Implement Infrastructure-as-Code (IaC) via Terraform, Helm and GitOps for code-based management of cloud and cluster resources, optimize CI/CD pipelines and strengthen release risk control. Lead end-to-end building and iteration of the SRE efficiency platform, develop in-house automation tools covering intelligent capacity assessment, automatic cluster scaling, fault self-healing and full-lifecycle change control. Integrate with cloud platforms, K8s APIs and business middle-ware interfaces to enable automated collection, cleansing, analysis and visualization of monitoring, resource and business data across domains. Implement chaos engineering systems and develop custom fault injection tools to verify system fault tolerance and resilience across multiple dimensions and expose architectural risks in advance.

4. Capacity Planning, Performance Tuning & FinOps Cost Governance

Build standardized capacity assessment frameworks, develop traffic and resource measurement models, and define scaling plans for daily and emergency scenarios. Lead capacity estimation, pressure test design, cluster scaling and peak-time on-call support for marketing campaigns and high-traffic scenarios, conduct end-to-end bottleneck remediation to continuously improve system throughput and response efficiency. Establish cost efficiency metrics, carry out governance of cluster redundancy, idle resource reclamation and elastic scheduling optimization to balance stability and resource cost. Optimize K8s scheduling strategies and elastic scaling rules to improve overall cluster resource utilization.

5. SRE Tooling Development

Independently develop stability components, capacity measurement modules, cost statistics systems, link inspection & monitoring plugins and automation efficiency tools using Java/Go, to automate capacity forecasting, resource analysis, fault handling and cost accounting, reduce manual O&M overhead and bridge the gap between R&D and operations.

6. AI-Powered SRE System Construction

Benchmark AI O&M and AI engineering efficiency systems from Alibaba and Ant Group. Implement AI capabilities including intelligent anomaly detection, AI root-cause analysis, change risk prediction and traffic peak forecasting based on large language models and time-series algorithms. Build AI O&M agents, intelligent pipelines, AI-driven change risk control and intelligent scheduling capabilities to realize alert noise reduction, automated fault attribution and automatic ticket handling. Shift SRE from reactive fire-fighting to proactive AI risk prevention, and implement AI + FinOps intelligent resource governance.

Job Requirements:

• Minimum Bachelor's or higher in Information Technology, Engineering or any related discipline.

• Proficient in at least one backend language (Java or Go), with solid programming fundamentals, data structure and algorithm knowledge and data structure and algorithm knowledge and proven engineering R&D experience. Capable of independently completing requirement decomposition, solution design, coding, unit testing and online rollout. Familiar with RESTful API design, MySQL, Redis and other SQL/NoSQL databases; experienced in backend API development, feature iteration and tool/platform module development. Skilled in Shell/Python scripting for fast delivery of automation scenarios.

• Minimum 3 years of SRE/DevOps experience in large-scale enterprises, with hands-on experience in large-scale cloud-native distributed clusters and global business operation. Solid knowledge of Linux kernel, process scheduling, network models and performance tuning; proven track record of troubleshooting complex online incidents and root-cause analysis. Proficient in Docker and Kubernetes core principles and production O&M, including cluster scheduling, resource management, node maintenance and container troubleshooting. Familiar with Istio/Envoy service mesh, including traffic gray release, rate limiting, circuit breaking, fault injection and link governance. Experienced in Prometheus, Grafana, ELK and other observability stacks; able to design end-to-end monitoring metrics, tiered alerting rules and log collection specifications. Familiar with CI/CD tools such as GitLab CI and ArgoCD with pipeline construction and optimization experience. Hands-on IaC practice with Terraform, Helm and GitOps. Understand cloud billing rules of AWS and Tencent Cloud, with practical experience in capacity planning, performance tuning and FinOps cost governance.

• Data-driven mindset to make decisions on stability, efficiency and cost based on metrics. Strong ability for incident response and root-cause analysis, capable of cross-team collaboration with R&D and product teams to close issues. Global perspective to balance stability, performance and cost. Technical influence to roll out SRE standardization and reliability culture. Strong ownership to proactively identify risks and drive continuous optimization initiatives.

Wong Shu Teng Joey

EA License: 23C2060

Reg ID: R2095170

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