Senior SRE Engineer

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