Senior Site Reliability Engineer

OfficeSpace Software is an AI workplace management platform that helps teams optimize their performance in the modern workplace. They are seeking a Senior Site Reliability Engineer to own the performance, reliability, and cost efficiency of their production platform, driving improvements and leading the transition to AI-assisted reliability engineering.

Responsibilities:

• Drive measurable improvements in latency, throughput, and availability across a large-scale production environment
• Own system performance—from Linux internals to Kubernetes scheduling—and eliminate bottlenecks before customers feel them
• Define and enforce SLIs, SLOs, and error budgets that balance speed, reliability, and growth
• Partner with application engineers to profile code paths, improve execution efficiency, and harden services under real load
• Lead database performance optimization across queries, indexing, replication, and workload isolation
• Design and oversee AI-assisted load testing, stress testing, and capacity planning workflows
• Guide the migration from monolithic deployments to multi-tenant Kubernetes platforms
• Reduce infrastructure spend through architectural decisions, right-sizing, and intelligent scaling strategies
• Build and supervise automation for infrastructure provisioning, configuration management, and observability
• Set clear operational standards for reliability, performance, and incident response—and raise the bar for how we run production

Requirements:

• 7+ years operating and evolving large-scale production systems
• Deep Linux systems expertise with hands-on performance tuning across CPU, memory, disk, and networking
• Strong Python skills for automation, tooling, and AI-assisted systems workflows
• Production experience with Ruby/Rails ecosystems, including Puma and Sidekiq
• Proven ability to diagnose and resolve complex database performance issues (MySQL/MariaDB or PostgreSQL)
• Advanced Kubernetes experience—workload sizing, scheduling, and multi-tenant operations
• Infrastructure-as-code mastery using Terraform and Terragrunt
• Experience with configuration management tools such as Puppet or Ansible
• Strong observability instincts across metrics, logs, and traces using tools like Prometheus, Grafana, Datadog, or ELK
• AI fluency—comfortable supervising AI agents for analysis, testing, and reporting, and validating their outputs
• A builder mindset. You move fast, take ownership, and raise standards
• Scaling and refactoring monolithic applications under real production load
• Extracting databases or stateful components from monoliths
• Apache and Nginx tuning at scale
• Redis performance optimization and operational management
• CI/CD systems and GitOps workflows, including ArgoCD
• Cloud cost optimization and FinOps-aligned operational practices