Staff Software Engineer, Temporal Technologies

• We’re looking for someone who thrives in ambiguity, enjoys turning reliability goals into concrete engineering work, and can lead cross-team efforts that make systems more resilient at scale
• Strong computer science fundamentals, especially in distributed systems, concurrency, and performance
• Demonstrated ability to design and build complex systems that operate reliably under high load and partial failure
• Experience driving reliability improvements across multiple services, not just within a single codebase
• Hands-on experience with at least one of: gamedays, chaos testing, load testing, or building reliability scorecards
• Strong judgment in ambiguous situations, including the ability to prioritize reliability work based on risk and impact
• Excellent communication skills, including the ability to align multiple stakeholders on reliability goals, plans, and tradeoffs
• A collaborative mindset and a track record of mentoring and leveling up engineering practices

Desirable

• Join our Reliability team as a Staff Software Engineer, where you’ll own the reliability of operating Temporal Cloud end to end
• You will help define and measure reliability expectations, harden systems through gamedays and chaos testing, and build the tooling and practices that make reliability visible and continuously improving across services and operational processes
• Own reliability outcomes for operating Temporal Cloud end to end, partnering across engineering, infrastructure, and product to drive measurable improvements
• Define, implement, and evolve reliability targets and associated practices, including alerting thresholds, operational readiness criteria, and escalation paths
• Plan and run gamedays to validate incident response, operational procedures, and cross-team coordination under realistic failure scenarios
• Build and scale a chaos testing program that exercises failure modes safely and drives remediation work that reduces real risk
• Define and maintain a reliability scorecard across services and key operational processes, and use it to prioritize reliability investments
• Lead load testing and performance testing efforts, including test design, tooling, and analysis of bottlenecks and capacity constraints
• Improve observability standards (metrics, logs, traces, dashboards) so reliability signals are consistent, actionable, and easy to audit
• Drive post-incident learning and corrective actions, ensuring fixes are durable and reduce recurrence risk over time
• Make system-level tradeoffs across reliability, performance, cost, and velocity, and document decisions clearly for long-term maintainability
• Mentor other engineers and raise the bar on reliability engineering practices across teams