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10+ years of engineering experience, including at least 3 years in SRE, production engineering, or a reliability-focused Staff Engineer role operating across multiple teams.

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Demonstrated experience owning reliability at a platform or organizational level rather than only for an individual service.

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Deep practical experience designing and implementing SLIs, SLOs, and error budgets, including successfully driving adoption across product and engineering teams.

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Strong incident leadership experience, including managing high-severity, customer-facing incidents and leading effective postmortems that result in measurable improvements.

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Advanced understanding of distributed-system failure modes, including database and cache saturation, cascading failures, retry storms, capacity constraints, graceful degradation, and load shedding.

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Strong hands-on experience with Kubernetes, AWS, and modern observability platforms such as Datadog or comparable technologies.

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Ability to read and write production code in Go, TypeScript, or a similar language, as well as work with infrastructure as code.

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Demonstrated ability to influence teams without direct authority and successfully change engineering practices across an organization.

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Strong coaching and mentoring skills, with evidence of developing engineers into effective reliability owners.

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Exceptional written and verbal communication skills, with the ability to clearly communicate incidents, risks, technical trade-offs, and reliability priorities to both engineers and executives.

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Strong preference for asynchronous, documented decision-making and clear technical communication.

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Practical experience using AI tools for incident investigation, telemetry analysis, runbook and postmortem development, and engineering tooling.

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Understanding of how operational data, alerts, dashboards, and runbooks should be structured to support safe AI-assisted diagnosis and operations.

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Pragmatic approach to reliability, with the ability to balance operational risk, engineering investment, delivery speed, and business priorities.

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Experience in fraud detection, identity, payments, or other real-time and adversarial environments is an asset.

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Experience with multi-region architectures, cell-based architectures, or failure-isolation strategies is a plus.

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Experience operating Elasticsearch, Redis, DynamoDB, or Kafka at scale and understanding their failure modes is beneficial.

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Familiarity with FinOps and cloud infrastructure cost-versus-reliability trade-offs is an advantage.

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Must be authorized to work from the hiring location; visa sponsorship is not provided.