Engineering Manager (Site Reliability Engineering)

• Replit enables people to build software with AI. The systems underneath that experience must support safe production changes, measurable reliability, and predictable performance as usage grows
• This Engineering Manager will lead SRE across observability, incident management, load testing, performance engineering, cloud cost and capacity, and rollout infrastructure. You’ll lead and grow an existing team that builds and operates production platforms and works hands-on across application and infrastructure boundaries
• This is a software-building leadership role, not simply an incident-management function. You’ll help teams ship safely, understand production behavior, and remove performance bottlenecks through concrete engineering improvements. You should be comfortable going deep on a rollout failure or performance investigation while developing technical leaders and sustainable ownership across a distributed team
• Observability. Build and operate metrics, logs, traces, and alerting capabilities. Help teams establish meaningful SLOs and use production telemetry to diagnose problems and verify improvements
• Incident Management. Own incident tooling and practices, coordinate cross-team response, and turn incident reviews into engineering improvements that reduce recovery time and repeat failures
• Load Testing. Build and maintain load/failure testing capabilities. Validate critical paths under expected demand, quantify headroom, and test recovery and production readiness with service owners
• Performance Engineering. Lead deep engagements with internal teams on SLOs and end-to-end performance. Use profiling, telemetry, and load tests to identify bottlenecks and deliver improvements with service owners—not just recommendations
• Stay technically engaged. Review designs and production changes, debug difficult failure modes, and use AI coding tools—including Replit—to prototype and automate. Apply rigorous review and verification to AI-generated changes
• Build and grow a high-ownership engineering team. Coach engineers, develop technical leaders, manage performance, and hire against agreed needs. Make distributed collaboration, mentoring, and backup coverage deliberate rather than relying on a few permanent escalation points
• Measure outcomes and close the loop. Track rollout safety, recovery time, repeat incidents, critical-path latency/throughput, test coverage, and improvements arising from cost/capacity analysis. Agree success measures and continuing ownership with partner teams

Benefits

• Flexible Work Hours
• Remote-First and Autonomous Working Environment
• Health, Dental, Vision, and Life Insurance
• Home Office Set-Up Stipend
• Short Term and Long Term Disability
• Monthly Expenses Stipend
• Flexible PTO (2 Weeks Minimum Required) + Holidays
• Annual Company/Team Offsites (4/year)
• 401k Program
• Commuter Benefits
• Parental and Baby Bonding Leave
• Equity- Platform-product and cross-team judgment. You can build capabilities other teams adopt, lead hands-on engagements without absorbing every service’s operations, and make clear tradeoffs among reliability, performance, engineering effort, and cost
• Safe-change and performance judgment. You have led consequential migrations or incidents and used measurement to diagnose reliability or performance problems. You can distinguish symptoms from causes and validate fixes under realistic conditions
• Demonstrated engineering management. You have led and developed engineers, made prioritization and performance decisions, hired thoughtfully, and delivered through a team—not only acted as its strongest individual contributor
• Software-oriented production systems depth. You have built and operated distributed systems or reliability platforms and can reason across deployment behavior, Kubernetes, telemetry, service dependencies, and recovery mechanisms
• Experience with GitOps or progressive-delivery platforms such as Harness, ArgoCD, or Kargo
• Experience with observability, profiling, load-testing, and failure-testing systems, including OpenTelemetry or comparable tooling
• Experience with cloud cost attribution, capacity planning, and provider coordination, particularly on GCP
• Experience growing distributed teams and using AI tools to increase engineering output while preserving production safeguards