Senior SRE Engineer
Established in 2018, Kronos Research is a quantitative trading firm that has become a leader in the industry, handling billions of dollars in daily transactions. They specialize in market making for both tokens and exchanges, proprietary trading, asset management, and venture capital investments within the crypto space.
About Kronos Research
Established in 2018, Kronos Research is a quantitative trading firm that handles billions of dollars in daily transactions. The company specializes in several areas including Token Market Making, where it partners with top crypto projects to provide liquidity; Exchange Market Making, using high-frequency and quantitative strategies to enhance liquidity and limit volatility; Proprietary Quant Trading, leveraging advanced infrastructure and research; Asset Management, offering returns through a multi-strategy approach; and Venture Investment, investing in and advising early-stage founders. Kronos Research works with numerous centralized and decentralized exchanges such as Binance, OKX, Kucoin, Uniswap, and Coinbase.
Skills
About the Role
As a Senior SRE Engineer, you will manage large-scale Linux environments, performing troubleshooting and root-cause analysis while writing maintainable Bash, Ansible, and Python automation. You will take part in on-call rotations for infrastructure, CI/CD, and production service incidents. You will operate HPC clusters built on Slurm along with usage analytics, auditing, and monitoring tools, and you will maintain and plan storage for compute environments using Lustre and NAS. You will manage multi-cloud environments across AWS, Alibaba Cloud, and GCP using Terraform and AWS CDK, and build and operate Docker and Kubernetes environments and their deployment workflows. You will operate a self-hosted GitLab server and Runner fleet, and design and operate CI/CD systems and deployment pipelines for research and other projects. You will also build internal AI platforms using LangChain, LangGraph, Bedrock, and Elasticsearch RAG, and 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 to drive a problem from discovery, root-cause investigation, decision-making, to delivery with minimal supervision
- Self-directed and able to identify and prioritize problems worth solving independently
Responsibilities
- Manage large-scale Linux environments including troubleshooting and root-cause analysis
- Write maintainable, hand-off-ready Bash, Ansible, and Python automation
- Provide on-call support for infrastructure, CI/CD, and production service incidents
- Operate HPC clusters using Slurm along with usage analytics, auditing, and monitoring tools
- Maintain and plan storage for compute environments using Lustre and NAS
- Manage multi-cloud environments across AWS, Alibaba Cloud, and GCP using Terraform and AWS CDK
- Build and operate Docker (ECS) and 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 using LangChain, LangGraph, Bedrock, and Elasticsearch RAG
- Develop MCP servers, chatbots, AI agents, and similar services