Senior Backend Engineer (SRE / Reliability & Performance)

Location: Taipei, Taiwan

Department: Engineering

About Appier

Appier (TSE: 4180) is an AI-native Agentic AI as a Service (AaaS) company that empowers businesses to create value through cutting-edge AdTech and MarTech solutions. Founded in 2012 with the vision of "Making AI Easy by Making Software Intelligent," Appier helps businesses turn AI into ROI through its Ad Cloud, Personalization Cloud, and Data Cloud—each powered by Agentic AI that enables autonomous, adaptive, and real-time decision-making. Today, Appier operates 17 offices across APAC, the US, and EMEA, and is listed on the Tokyo Stock Exchange. Learn more at www.appier.com.

 

About the role

Engineers at Appier build a wide range of platforms and services that interconnect data and AI with our customers and users—operating at scale where every millisecond and every nine of availability matters. As a Senior Backend Engineer (SRE / Reliability & Performance), you will sit at the intersection of backend development and site reliability engineering: designing and building scalable, performant backend services while owning the reliability, observability, and performance characteristics of large-scale, high-traffic systems (QPS > 10k). You will profile and tune systems end to end, lead the response to production incidents, and drive the engineering practices that keep our services fast and resilient as traffic grows. Seniority and title are determined by job-related skills, experience, and evaluation following the interview. We welcome international candidates to our teams. This position is ideally to be based in Taiwan.

 

Responsibilities

• Design and build scalable, reliable, and maintainable backend services and the components that support them
• Own system reliability and performance for high-traffic services, including SLO/SLA definition, error budgets, and capacity planning
• Profile, benchmark, and tune critical components to resolve latency, throughput, and scalability bottlenecks in medium-to-large systems (QPS > 10k)
• Diagnose and solve production traffic problems—load spikes, hot paths, resource contention, and cascading failures
• Lead system design and provide technical guidance on reliability and performance trade-offs
• Continuously improve observability (logging, metrics, tracing), incident management, DevOps, and production operational SOPs
• Lead incident response, troubleshooting, and blameless post-mortems, then drive the follow-up engineering work
• Build and optimize CI/CD pipelines and deployment automation to ship safely and frequently
• Lead code reviews to ensure high quality coding and operational standards
• Mentor engineers and facilitate agile collaboration across cross-functional teams
• Participate in on-call rotation to ensure product reliability and scalability

 

About you

[Minimum qualifications]

• 5+ years of experience in backend software development, with hands-on SRE / reliability / infrastructure responsibilities
• Proven experience tuning system reliability and performance for production services
• Demonstrated experience solving traffic and scalability problems in medium-to-large systems
• Ability to build and operate web services on Linux
• Proficient in one or more of the following languages: Go / Python / Java / Scala / C++
• Good knowledge of Network API design (e.g. REST or GraphQL)
• Good understanding of SQL/NoSQL databases (MySQL / PostgreSQL / MongoDB / Redis / etc.)
• Hands-on experience with observability tooling (e.g. Prometheus, Grafana, distributed tracing)
• Familiar with AWS, GCP, or Azure
• Familiar with Git
• Proactive, with strong interpersonal and problem-solving skills

[Preferred qualifications]

• BS/MS degree in Computer Science or related field
• Technical leadership experience, such as mentoring engineers and facilitating agile processes
• Strong skills with profiling and debugging tools, and building high-performance network services on Linux
• Experience designing and architecting large-scale distributed systems and implementing distributed algorithms and data structures
• Experience with container orchestration (Kubernetes, Docker) and infrastructure-as-code / configuration management (Terraform, Ansible)
• Hands-on experience with CI/CD platforms (Jenkins, GitLab CI, GitHub Actions, ArgoCD)
• Expert in some of the following CS domains:
• Nginx / HAProxy and load balancing
• Caching strategies and data-intensive application design
• Monitoring and alerting systems (Prometheus / Nagios)
• Capacity planning and chaos / resilience engineering
• Operation automation
• Continuous integration / continuous deployment

 

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