Sr. Backend Engineer (AI Threat Analysis Platform)
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趨勢科技 - 全球雲端資安領航者 / 全亞洲最大軟體公司 / 企業版圖橫跨五大洲 / 趨勢全球研發基地在台灣
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What You’ll Do
- Own the production operation of the platform end to end, including reliability, availability, performance, and cost
- Define SLOs and build monitoring, alerting, and incident response processes; lead on-call response and blameless postmortems
- Architect and evolve scalable backend systems that orchestrate multi-stage analysis workloads, including AI-driven components, and process results at scale
- Build and maintain CI/CD pipelines and Infrastructure as Code to enable safe, repeatable releases and rollbacks
- Monitor and optimize per-request cost across compute and AI inference; build cost visibility and anomaly detection
- Establish operational excellence practices: runbooks, capacity planning, load testing, and on-call rotation design that scales beyond a single owner
- Drive technical decisions on system architecture, technology stack, and infrastructure design
- Champion AI adoption to enhance development workflows and code quality
Qualification/Requirement
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related field
- 5+ years of backend development experience delivering and operating production systems at scale
- Hands-on experience owning production services, including on-call and incident handling through root cause analysis and follow-up actions
- Proficiency in at least one backend language
- Hands-on experience with microservices development and Kubernetes deployment
- Experience designing and managing CI/CD pipelines
- Cloud-based development experience (AWS preferred; Azure or GCP acceptable)
- Proficiency in Infrastructure as Code frameworks (Terraform, CloudFormation, or Pulumi)
- Experience designing observability (metrics, logs, tracing) and defining alerts, not only consuming existing dashboards
Nice to Have
- Experience operating services that depend on AI inference or external APIs (rate limits, retries, cost control), including LLM gateway, tracing, and evaluation tooling integrated into CI/CD pipelines
- Experience with workload isolation or secure execution environments
- Experience with queue-based or asynchronous processing systems at scale (Kafka, SQS, or similar)
- Experience with resource estimation, capacity planning, and cost optimization in the cloud
- Ability to drive cross-team adoption of operational practices such as on-call, SLOs, and postmortems
- Expertise in containerization (Docker) and DevOps/SRE practices
- Proficiency with AI development tools (Claude Code, Cursor)
- Experience in security product or cybersecurity domain
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連結智慧 守護世界 --- Connected Intelligence for Securing a Connected World