Site Reliability Engineer

SREs at Fluidstack sit at the core of our infrastructure, working across software, hardware, and operations to ensure the reliability and performance of our global GPU cloud. They partner closely with teams including networking, platform engineering, and data center operations to build systems that scale with the demands of AI workloads. SREs are hands-on and possess deep systems knowledge and strong communication skills. You’ll be responsible for tackling complex production issues, deploying resilient infrastructure, and continuously improving the stability and observability of our platform as we grow.

A typical day may involve:

Deploying clusters of 1,000+ GPUs using custom written playbooks; modifying these tools as necessary to provide the perfect solution for a customer. Validating correctness and performance of underlying compute, storage, and networking infrastructure, and working with providers to optimize these subsystems. Migrating petabytes of data from public cloud platforms to local storage, as quickly and cost effectively as possible. Debugging issues anywhere in the stack, from “this server’s fan is blocked by a plastic bag” to “optimizing S3 dataloaders from buckets in different regions”. Building internal tooling to decrease deployment time and increase cluster reliability, including automation where the customer benefits clearly outweigh the implementation overhead.

This role will involve being part of an on-call rotation up to one week per month. Focus

A customer-centric attitude, an accountability mindset, and a bias to action. A track record of shipping clean, well-documented code in complex environments. An ability to create structure from chaos, navigate ambiguity, and adapt to the dynamic nature of the AI ecosystem. Strong technical and interpersonal communication skills, a low ego, and a positive mental attitude.

Minimum Requirements 5+ years of SRE, DevOps, Sysadmin, and/or HPC engineering experience.

Great verbal and written communication skills in English. Experience deploying and operating Kubernetes and/or SLURM clusters. Experience in writing Go, Python, Bash. Experience using Ansible, Terraform, and other automation or IAC tools. Strong engineering background, preferably in Computer Science, Software Engineering, Math, Computer Engineering, or similar fields.

Nice To Haves

You have built and operated an AI workload at 1000+ GPU scale. You have built multi-tenant, hyperscale Kubernetes based services. You have physically deployed infrastructure in a datacenter, managed bare metal hardware via MaaS or Netbox, etc. You have deployed and managed multi-tenant InfiniBand or RoCE networks. You have deployed and managed petabyte scale all-flash storage systems, including DDN, VAST, and/or Weka; or Ceph, LUSTRE, or similar open source tools.

Competitive total compensation package (salary + equity). Retirement or pension plan, in line with local norms. Health, dental, and vision insurance. Generous PTO policy, in line with local norms.

The base salary range for this position is $175,000 - $320,000 per year, depending on experience, skills, qualifications, and location. This range represents our good faith estimate of the compensation for this role at the time of posting. Total compensation may also include equity in the form of stock options.

We are committed to pay equity and transparency. Fluidstack is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. Fluidstack will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law. #J-18808-Ljbffr

About Fluidstack At Fluidstack, we build the compute, data centers, and power that will fuel artificial superintelligence. We supply GWs of compute capabilities to the world’s biggest AI Labs at industry-defining speeds. Our team is small, fast, and obsessed with quality. We own outcomes end-to-end, challenge assumptions, and treat our customers’ problems as our own. No task is beneath anyone here. There are a few thousand people who will shape the trajectory of superintelligence. Come and be one of them.