Site Reliability Engineer, Algolia

• Hands-on production knowledge of AWS or GCP
• Practical Kubernetes knowledge and an interest in operating it in production
• Familiarity with infrastructure as code, ideally Terraform
• Programming or scripting skills in Python, Go, or an equivalent language
• Strong Linux and networking fundamentals
• A strong interest in reliability, automation, and solving production problems
• Comfort adopting AI-assisted engineering tools, with sound judgement for critical production systems
• The ability to communicate clearly and work effectively with a distributed team
• Excellent spoken and written English skills

Desirable

• The Infrastructure as a Service team is at the center of one of Algolia’s most consequential engineering transformations
• For years, Algolia has operated a production fleet of approximately 4,000 bare-metal servers to deliver the reliability, low latency, and scalability that our customers expect
• We are now building the foundations of a unified cloud and Kubernetes platform designed to support Algolia’s growth for years to come
• . We are now building the foundations of a unified cloud and Kubernetes platform designed to support Algolia’s growth for years to come
• This is not a lift-and-shift project. It is an opportunity to rethink how Algolia provisions, secures, operates, observes, upgrades, and scales production infrastructure and to build it as a platform that engineers can safely consume, rather than a queue of manual requests
• As a Site Reliability Engineer in IaaS, you will help build the next generation of Algolia’s production infrastructure
• You will contribute to the cloud baseline and reliable lifecycle capabilities that enable teams to operate and migrate workloads safely on a cloud-native platform
• You will work across cloud foundations, Kubernetes, automation, reliability, and large-scale production operations
• As a P3 engineer, you will be a hands-on contributor. You will build, operate, and improve production infrastructure while developing deep expertise in cloud, Kubernetes, reliability, and automation
• Build and improve Cloud Baseline capabilities, including identity and access, networking, security, resource inventory, tagging, and auditability
• Develop and maintain infrastructure as code and automation for cloud environments and Kubernetes infrastructure
• Contribute to reliable, repeatable cloud and cluster lifecycle operations
• Help build self-service capabilities, reusable modules, and clear documentation that make the safe path the easy path for platform consumers
• Reduce manual work and configuration drift through automation, testing, GitOps practices, and standardisation
• Use automation and AI-assisted engineering tools where appropriate to improve infrastructure analysis, documentation, and safe, repeatable changes
• Improve observability, monitoring, alerting, capacity management, and operational documentation
• Investigate production issues, participate in the on-call rotation, and turn lessons learned into lasting improvements
• Work with Infrastructure, Security, FinOps, and engineering teams to deliver reliable, secure, and cost-aware platform capabilities