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Senior SRE Engineer

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Last seen by MeritLog September 7, 2026Source: GreenhouseSource version: greenhouse-job-board-v1

Source: the employer's Greenhouse job board. Open the original listing for current details. Availability is not verified for this retained page.

Job details

Work model: On-site
Salary: Not listed by source
Location: Taiwan

What the role asks for

What you'd do

Manage large-scale Linux environments: troubleshooting and root-cause analysis
Write maintainable, hand-off-ready Bash / Ansible / Python automation
On-call for infrastructure, CI/CD, and production service incidents
Operate HPC clusters (Slurm) along with usage analytics, auditing, and monitoring tools
Maintain and plan storage for compute environments (Lustre, NAS)
Manage multi-cloud environments (AWS, Alibaba Cloud, GCP) with Terraform / AWS CDK
Build and operate Docker (ECS) / Kubernetes (EKS) environments and their deployment workflows
Operate self-hosted GitLab server and Runner fleet
Operate CI/CD systems and design deployment pipelines for research and other projects
Build internal AI platforms (LangChain / LangGraph / Bedrock, Elasticsearch RAG)
Develop MCP servers, chatbots, AI agents, and similar services

What they're asking for

**5+ years** of hands-on Linux systems administration and infrastructure operations experienceExperience
Solid Linux internals knowledge (process / memory / filesystem / networking / systemd / cgroup); able to localize issues even without complete logsSkill
Strong Bash / Shell scripting skills - able to write maintainable scripts that others can pick upSkill
Programming ability for data processing, CLI tools, and API services; Python proficiency preferredSkillPreferred
Solid storage fundamentals with hands-on experience: RAID levels and rebuild trade-offs, filesystem selection, snapshot and backup planning; NAS / shared storage (NFS / SMB) operations experienceSkill
Experience with at least one major public cloud (AWS / GCP / Alibaba Cloud) and IaC tooling (Terraform / CDK / Ansible)Skill
Familiar with containerization and orchestration (Docker, Kubernetes)Skill
CI/CD pipeline design and operations experience (GitLab CI / Jenkins / Airflow)Skill
Able to own a cross-service subsystem end-to-end: design, implementation, documentation, handoffSkill
**Strong autonomy**: can drive a problem from discovery, root-cause investigation, decision-making, to delivery with minimal supervision; able to make judgment calls under incomplete information and proactively communicate progress, risks, and rationaleSkill
**Self-directed**: doesn't wait for tickets - identifies problems worth solving and prioritizes them independentlySkill
HPC scheduler experience (Slurm / PBS / LSF)SkillPreferred
Parallel filesystem operations experience (Lustre / GPFS / BeeGFS)SkillPreferred
Advanced Linux performance analysis (perf, eBPF, ftrace) and kernel parameter tuningSkillPreferred
DB operations experience (MySQL, ClickHouse)SkillPreferred
Low-latency network tuning and cross-datacenter link optimizationSkillPreferred
LLM application development (LangChain, RAG, Agent, MCP)SkillPreferred
Self-managed Kubernetes experience (Kubespray, kubeadm)SkillPreferred
GPU server operations (single-node): NVIDIA driver / CUDA toolkit version management, `nvidia-smi` / DCGM monitoring, nvidia-container-toolkit integration, troubleshooting XID / ECC errors and thermal throttlingSkillPreferred

Parsed by MeritLog from the employer’s own posting. The full description follows below.

Job description

Responsibilities Linux Systems & Automation (Core) - Manage large-scale Linux environments: troubleshooting and root-cause analysis - Write maintainable, hand-off-ready Bash / Ansible / Python automation - On-call for infrastructure, CI/CD, and production service incidents HPC Cluster & Storage - Operate HPC clusters (Slurm) along with usage analytics, auditing, and monitoring tools - Maintain and plan storage for compute environments (Lustre, NAS) Cloud & Hybrid Infrastructure - Manage multi-cloud environments (AWS, Alibaba Cloud, GCP) with Terraform / AWS CDK - Build and operate Docker (ECS) / Kubernetes (EKS) environments and their deployment workflows CI/CD & Developer Experience - Operate self-hosted GitLab server and Runner fleet - Operate CI/CD systems and design deployment pipelines for research and other projects GenAI / Internal Platform - Build internal AI platforms (LangChain / LangGraph / Bedrock, Elasticsearch RAG) - Develop MCP servers, chatbots, AI agents, and similar services Requirements - **5+ years** of hands-on Linux systems administration and infrastructure operations experience - Solid Linux internals knowledge (process / memory / filesystem / networking / systemd / cgroup); able to localize issues even without complete logs - Strong Bash / Shell scripting skills - able to write maintainable scripts that others can pick up - Programming ability for data processing, CLI tools, and API services; Python proficiency preferred - Solid storage fundamentals with hands-on experience: RAID levels and rebuild trade-offs, filesystem selection, snapshot and backup planning; NAS / shared storage (NFS / SMB) operations experience - Experience with at least one major public cloud (AWS / GCP / Alibaba Cloud) and IaC tooling (Terraform / CDK / Ansible) - Familiar with containerization and orchestration (Docker, Kubernetes) - CI/CD pipeline design and operations experience (GitLab CI / Jenkins / Airflow) - Able to own a cross-service subsystem end-to-end: design, implementation, documentation, handoff - **Strong autonomy**: can drive a problem from discovery, root-cause investigation, decision-making, to delivery with minimal supervision; able to make judgment calls under incomplete information and proactively communicate progress, risks, and rationale - **Self-directed**: doesn't wait for tickets - identifies problems worth solving and prioritizes them independently Nice to Have - HPC scheduler experience (Slurm / PBS / LSF) - Parallel filesystem operations experience (Lustre / GPFS / BeeGFS) - Advanced Linux performance analysis (perf, eBPF, ftrace) and kernel parameter tuning - DB operations experience (MySQL, ClickHouse) - Low-latency network tuning and cross-datacenter link optimization - LLM application development (LangChain, RAG, Agent, MCP) - Self-managed Kubernetes experience (Kubespray, kubeadm) - GPU server operations (single-node): NVIDIA driver / CUDA toolkit version management, `nvidia-smi` / DCGM monitoring, nvidia-container-toolkit integration, troubleshooting XID / ECC errors and thermal throttling - Experience or familiarity with integrating GPU resources into Slurm: GRES configuration, cgroup-based GPU isolation, user/job-level resource limits

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