Staff SRE, AI Infrastructure

📋 Description

• Improve observability, automation, deployment safety, capacity planning, and incident learning
• Help teams adopt effective SLOs and production-readiness practices
• Troubleshoot complex failures spanning compute, networking, storage, and distributed workloads
• Improve GPU node health detection and automated recovery
• Strengthen the resilience of distributed AI training
• Develop continuous GitOps delivery using platforms such as Argo CD or Flux

🎯 Requirements

• Hands-on experience owning the reliability of large-scale cloud, Kubernetes, or distributed
• Recent experience coding, automating, configuring, or troubleshooting production systems
• Comfortable working in Python or Go
• Proficiency with infrastructure as code, CI/CD or GitOps, and modern observability practices
• Understanding of distributed-systems failure modes across compute, networking, and storage
• Ability to demonstrate measurable improvements to reliability, performance, capacity, or cost

🎁 Benefits

• Salaries benchmarked against the market annually
• Meaningful equity
• Relocation support and visa sponsorship where applicable
• Hybrid working and core hours
• Learning and development budgets
• Comprehensive benefits including health insurance, dental, enhanced maternity and paternity leave