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Lambda

Senior Site Reliability Engineer - Storage

Lambda is hiring a Senior Site Reliability Engineer - Storage. It pays $267k-$356k a year and Level rates it ; you can apply on Lambda.

Level's read on this job

  • Level rates this role Works on AI ●●●○: the daily work is on AI products, without building the model.
  • Some of the work can be done remotely, according to the posting.
  • The posting mentions Ansible, Jenkins and storage among its tools and skills.
  • Level classes it as a senior role.
  • Lambda has 96 other open roles on Level.

AI in this role

Own the reliability, performance, and capacity health of production storage fleet powering AI compute workloads.

AnsibleJenkins
storagesrelinuxnetworkingci-cd

Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers. Our customers range from AI researchers to enterprises and hyperscalers. Lambda's mission is to make compute as ubiquitous as electricity and give everyone the power of superintelligence. One person, one GPU.

If you'd like to build the world's best AI cloud, join us.

*Note: This position requires presence in our San Francisco or San Jose office location 4 days per week; Lambda’s designated work from home day is currently Tuesday.


Lambda's Storage Engineering team is the backbone behind our world-class storage offerings, operating at a scale seldom seen in today's markets. We own the full spectrum of Lambda's data platform services—from low-level storage systems to the APIs and tooling our customers build on every day.

Our work directly powers some of the most demanding compute workloads in the industry, which means reliability and performance aren't just goals—they're the baseline. We're looking for engineers who want to solve problems at scale, own critical systems end to end, and help shape the future of infrastructure for AI and beyond

What You’ll Do

  • Own the reliability, performance, and capacity health of Lambda's production storage fleet across all data centers, operating behind Lambda's own software-defined data plane.

  • Build and maintain monitoring, dashboards, and alerting for storage performance, capacity, and hardware failures.

  • Investigate and resolve storage-related incidents using deep telemetry, logs, and performance profiling — from a single flapping NIC to a cluster-wide rebuild.

  • Automate ticketing, escalation, and incident-response workflows so the team spends less time on repetitive triage and more time on root cause.

  • Design and maintain self-healing automation for common failure modes: drive replacement, node swaps, rebuild monitoring, and capacity rebalancing.

  • Implement CI/CD pipelines for storage automation and tooling.

  • Partner with Storage Engineers, Fleet Orchestration, and Release Engineering to automate the deployment and configuration of software-defined storage across new and existing sites using tools such as Ansible, Jenkins etc.

  • Work with hardware and networking teams to diagnose low-level I/O and network issues — NIC errors, RDMA/RoCE/InfiniBand fabric health, path multipathing — that surface as storage-layer symptoms.

  • Participate in an on-call rotation supporting Lambda's storage fleet, with a focus on driving down MTTR and building the automation that keeps you from getting paged for the same thing twice.

You Have

  • 5+ years of experience operating Linux systems in production or HPC environments, with hands-on storage experience at scale on scale-out or software-defined platforms (e.g., CEPH, Lustre, GPFS, or similar).

  • Hands-on experience operating Software-Defined Storage (SDS) platforms at scale, including integrating with their management and data-plane APIs.

  • Strong incident-response instincts: comfortable owning a production storage incident end to end, from first alert through root cause to postmortem.

  • Working experience with monitoring and logging platforms such as Prometheus, Grafana, Alertmanager, Datadog, or SumoLogic — including building dashboards and alert/pager routing for multiple audiences.

  • Working experience with Kubernetes (GitOps tooling such as ArgoCD, Helm/Kustomize) and hands-on troubleshooting.

  • Working experience with CI/CD tooling (GitHub Actions, Jenkins, BuildKite), containerization (Docker/Podman), and systems programming in Python or Go.

  • Working experience with Infrastructure as Code (Terraform, Ansible).

  • Solid understanding of core storage protocols across file (NFS, SMB), object (S3), block (NVMe-oF/TCP), and structured (vector DB, SQL) storage.

Nice to Have

  • Experience with cutting-edge software-defined storage solutions such as VAST or Weka.

  • Enterprise storage expertise in solutions such as NetApp, Dell PowerScale, GPFS, or Lustre.

  • Experience writing or operating Kubernetes CSI drivers.

  • Experience with SR-IOV and virtualization (KVM/QEMU).

  • Experience with GPUDirect Storage, RDMA, InfiniBand, or RoCE networking.

  • Familiarity with NIC-level diagnostics (ethtool, mlxlink) and fleet-wide operations tooling (clush or similar).

  • Contributions to open-source storage projects.

Salary Range Information

The annual salary range for this position has been set based on market data and other factors. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description.

About Lambda

  • Founded in 2012, with 500+ employees, and growing fast

  • Our investors notably include TWG Global, US Innovative Technology Fund (USIT), Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, Gradient Ventures, Mercato Partners, SVB, 1517, and Crescent Cove

  • We have research papers accepted at top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG

  • Our values are publicly available: https://lambda.ai/careers

  • We offer generous cash & equity compensation

  • Health, dental, and vision coverage for you and your dependents

  • Wellness and commuter stipends for select roles

  • 401k Plan with 2% company match (USA employees)

  • Flexible paid time off plan that we all actually use

Equal Opportunity Employer

Lambda is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.

How we rate this

Senior Site Reliability Engineer - Storage at Lambda rates 60 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

StorageSreLinuxNetworkingCI/CDAnsibleJenkins

Questions you could be asked

  1. Tell me about a project where storage was part of your work. What did you do?
  2. Tell me about a project where sre was part of your work. What did you do?
  3. Tell me about a project where linux was part of your work. What did you do?
  4. Tell me about a project where networking was part of your work. What did you do?
  5. Tell me about a project where ci/cd was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: Storage, Sre, Linux, Networking, and CI/CD. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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