
Senior Software Engineer, Backend Development(Ad Cloud Serving Services)
- Taipei City
- Permanent
- Full-time
- Lead the design and development of scalable, high-performance, and reliable backend services for real-time ad recommendation, data serving, and core ad tech infrastructure.
- Drive technical roadmap and ownership for sizable projects, ensuring the delivery of robust and efficient solutions within the Ad Cloud ecosystem.
- Optimize critical system components for latency, throughput, and resource utilization, including database interactions (e.g., MongoDB sharding, ClickHouse optimizations) and network architecture.
- Enhance system observability, incident management, and operational excellence by implementing comprehensive monitoring, alerting (e.g., Grafana, Prometheus), and refining production SOPs.
- Collaborate closely with product managers and scientists to translate business requirements into technical designs and ensure seamless integration.
- Champion code quality through rigorous code reviews and adherence to best practices in system design and implementation.
- Mentor and guide junior engineers, fostering their growth in backend development best practices, distributed systems, and agile methodologies.
- Actively participate in on-call rotation within the Backend team to maintain product reliability and scalability for critical serving services.
- Contribute to a culture of continuous improvement, initiating team-level technical discussions, process enhancements, and knowledge sharing.
- 3-5+ years of hands-on experience in backend software development, particularly with high-performance, high-concurrency systems.
- Proficient in one or more of the following languages: Go, Python.
- Strong experience in system design and architecture for scalable and distributed systems, especially within a Linux environment.
- Good understanding of Network API Design (e.g., RESTful APIs, gRPC) and experience with message queues (e.g., Kafka, Pub/Sub) for data pipelines.
- Solid knowledge of SQL/NoSQL databases (e.g., MySQL, MongoDB, Redis, ClickHouse, PostgreSQL) and experience with database optimization and scaling strategies.
- Familiarity with DevOps practices, including CI/CD pipelines, Docker, Kubernetes, and cloud platforms (AWS, GCP, or Azure).
- Experience with observability tools (e.g., Prometheus, Grafana) and implementing robust monitoring and alerting.
- Proactive, excellent problem-solving skills, and strong communication in a cross-functional team setting.
- BS/MS degree in Computer Science or a related field.
- Demonstrated ability to refactor complex systems, improve performance metrics (e.g., latency, error rate, CPU usage), and optimize resource utilization.
- Familiarity with A/B testing frameworks and supporting customizable configurations for model iteration.
- Hands-on experience with deploying and serving machine learning models in production environments.
- Exposure to ad-tech or recommendation systems is a plus.