Senior Site Reliability Engineer

Fleetio is a modern software platform that helps organizations manage their fleet operations. The Senior Site Reliability Engineer will run, maintain, and improve the performance, reliability, and scalability of Fleetio's Ruby on Rails application stack, infrastructure, and databases while developing AI-driven workflows to reduce operational toil.

Responsibilities:

• Proactively identify, triage, and resolve performance issues
• Enhance system observability by monitoring performance metrics across Ruby, Rails, and database systems, including SLOs and SLIs
• Build and maintain AI agents, skills, and automations that reduce operational toil across incident response, triage, and routine maintenance
• Use AI-assisted tooling to accelerate performance analysis, root-cause investigation, and code review
• Collaborate with other SREs to proactively identify and address performance bottlenecks
• Help product engineers adopt AI-driven workflows for performance and reliability best practices
• Lead database capacity planning and upgrade initiatives
• Manage the database-specific components of disaster recovery planning and execution
• Oversee backup systems and pre-production databases
• Create and maintain infrastructure and operations documentation, including runbooks and context that both engineers and AI agents can act on
• Participate in the on-call rotation

Requirements:

• Our ideal candidate is an Infrastructure Engineer experienced in scaling Ruby on Rails applications, with a passion for optimization and performance improvements
• You bring a strong background in Site Reliability and Infrastructure Engineering for Rails applications
• You follow Agile and DevOps principles, can effectively influence teams to achieve goals, and demonstrate excellent problem-solving skills in our fast-paced environment
• You're curious about how AI is changing infrastructure and reliability work, and you're eager to shape how a platform team puts it to use
• 5+ years of Ruby/Rails Experience
• 3+ years of AWS Experience
• Kubernetes experience
• Experience with profiling and benchmarking source code
• Effective at code review and identifying potential performance problems before they reach production
• Experience with Datadog or other APM tools
• Excellent written and verbal communication skills
• Experience building AI agents, LLM-powered automations, or integrations (e.g., using tool/function calling or MCP) for engineering or operations workflows
• Infrastructure as Code tools (Terraform)
• Deep understanding of cloud network fundamentals (routing, firewalls, load balancers, CDNs, VPCs, etc.)
• Experience with distributed event and data stores, such as Kafka, Redis, Elasticsearch, Memcached, and TimescaleDB
• You know a thing or two about the fleet management industry