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