Observability Backend Engineer Globalization
Location: Singapore
Function: Backend Engineering / Infrastructure / Observability
Levels: Up to Principal/Staff Engineer Level
About The Role
Our client is a globally scaling consumer internet platform serving hundreds of millions of users across content, community, e-commerce, and advertising ecosystems. As the company expands internationally and invests in AI-driven infrastructure, observability is critical for ensuring system reliability, performance, and compliance across regions. This role is focused on building next-generation observability systems, supporting both traditional distributed systems and emerging AI infrastructure, to ensure global platform stability and support future AI-native workloads.
Key Responsibilities
Lead the development of the observability stack across four core pillars: metrics, logging, tracing, and profiling. Build foundational observability capabilities across the full technology stack. Design and develop observability-related platforms and systems, including: Monitoring platforms End-to-end distributed tracing systems Logging services Computation engines (e.g., streaming analytics, real-time alerting, time-series analysis) Alerting systems eBPF-based observability capabilities Own both architecture design and product-level implementation. Ensure observability infrastructure operates with high performance, high availability, and stability under high-concurrency workloads. Continuously optimize systems and platforms through iterative improvements. Support both domestic and international observability architecture, data compliance requirements, and infrastructure stability initiatives. Drive the implementation of AI infrastructure and application observability, and 'Observability + AI' capabilities. Improve the stability of AI-driven systems and the efficiency and usability of traditional observability platforms.
Requirements
Education & Experience
Bachelor's degree or above in Computer Science or related field. Minimum 3+ years of relevant experience.
Backend Engineering Fundamentals
Strong proficiency in Java or Go. Solid understanding of concurrent programming, distributed systems, and performance optimization. Strong coding fundamentals.
Observability Ecosystem Expertise
Hands-on experience with cloud-native observability technologies, including but not limited to: OpenTelemetry CAT SkyWalking Prometheus VictoriaMetrics ELK stack ClickHouse eBPF Understanding of Kubernetes fundamentals and practical usage.
Core Systems Knowledge
Familiarity with foundational infrastructure components, including: Linux Networking Storage systems Message queues (MQ) Deep understanding of implementation principles is preferred.
(Preferred) AI-Related Experience
Familiarity with AI-related technologies and ecosystems, including but not limited to: PyTorch Spring AI Langfuse OpenClaw
Problem Solving & Collaboration
Strong ability to identify and solve complex technical problems. Ability to summarize and abstract technical learnings. Strong cross-team collaboration capability.
Mindset & Drive
Strong curiosity and interest in emerging technologies. High sense of ownership and accountability. Ability to work effectively under pressure.
Language Requirements
Fluent in both English and Chinese. Able to collaborate effectively in a global, bilingual engineering environment.
Location Requirement
For Singapore-based roles, Singapore Citizens / PRs preferred.
Why This Role
Opportunity to build observability systems at massive scale across global infrastructure. Work on cutting-edge areas combining distributed systems, cloud-native observability, and AI infrastructure. Direct exposure to AI observability, a scarce and high-value niche. Opportunity to shape next-generation observability platforms for global expansion. Due to volume of applicants, only shortlisted candidates will be contacted
EA Licence No.: 25S3232
EA Personnel Reg. No.: R1874604
EA Personnel Name: Kenneth Ho
Function: Backend Engineering / Infrastructure / Observability
Levels: Up to Principal/Staff Engineer Level
About The Role
Our client is a globally scaling consumer internet platform serving hundreds of millions of users across content, community, e-commerce, and advertising ecosystems. As the company expands internationally and invests in AI-driven infrastructure, observability is critical for ensuring system reliability, performance, and compliance across regions. This role is focused on building next-generation observability systems, supporting both traditional distributed systems and emerging AI infrastructure, to ensure global platform stability and support future AI-native workloads.
Key Responsibilities
Lead the development of the observability stack across four core pillars: metrics, logging, tracing, and profiling. Build foundational observability capabilities across the full technology stack. Design and develop observability-related platforms and systems, including: Monitoring platforms End-to-end distributed tracing systems Logging services Computation engines (e.g., streaming analytics, real-time alerting, time-series analysis) Alerting systems eBPF-based observability capabilities Own both architecture design and product-level implementation. Ensure observability infrastructure operates with high performance, high availability, and stability under high-concurrency workloads. Continuously optimize systems and platforms through iterative improvements. Support both domestic and international observability architecture, data compliance requirements, and infrastructure stability initiatives. Drive the implementation of AI infrastructure and application observability, and 'Observability + AI' capabilities. Improve the stability of AI-driven systems and the efficiency and usability of traditional observability platforms.
Requirements
Education & Experience
Bachelor's degree or above in Computer Science or related field. Minimum 3+ years of relevant experience.
Backend Engineering Fundamentals
Strong proficiency in Java or Go. Solid understanding of concurrent programming, distributed systems, and performance optimization. Strong coding fundamentals.
Observability Ecosystem Expertise
Hands-on experience with cloud-native observability technologies, including but not limited to: OpenTelemetry CAT SkyWalking Prometheus VictoriaMetrics ELK stack ClickHouse eBPF Understanding of Kubernetes fundamentals and practical usage.
Core Systems Knowledge
Familiarity with foundational infrastructure components, including: Linux Networking Storage systems Message queues (MQ) Deep understanding of implementation principles is preferred.
(Preferred) AI-Related Experience
Familiarity with AI-related technologies and ecosystems, including but not limited to: PyTorch Spring AI Langfuse OpenClaw
Problem Solving & Collaboration
Strong ability to identify and solve complex technical problems. Ability to summarize and abstract technical learnings. Strong cross-team collaboration capability.
Mindset & Drive
Strong curiosity and interest in emerging technologies. High sense of ownership and accountability. Ability to work effectively under pressure.
Language Requirements
Fluent in both English and Chinese. Able to collaborate effectively in a global, bilingual engineering environment.
Location Requirement
For Singapore-based roles, Singapore Citizens / PRs preferred.
Why This Role
Opportunity to build observability systems at massive scale across global infrastructure. Work on cutting-edge areas combining distributed systems, cloud-native observability, and AI infrastructure. Direct exposure to AI observability, a scarce and high-value niche. Opportunity to shape next-generation observability platforms for global expansion. Due to volume of applicants, only shortlisted candidates will be contacted
EA Licence No.: 25S3232
EA Personnel Reg. No.: R1874604
EA Personnel Name: Kenneth Ho