Observability Backend Engineer - Globalization

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