Staff Site Reliability Engineer

Accountabilities

• Define and implement SLIs and SLOs for critical production request paths, ensuring reliability objectives are visible, measurable, reviewed, and connected to engineering decisions.


• Introduce and champion error budgets as a practical framework for balancing reliability investments with product and feature delivery.


• Establish and maintain the reliability metrics used by engineering leadership to evaluate progress and identify areas requiring investment.


• Strengthen the complete incident management lifecycle, including detection, response, communication, escalation, postmortems, and follow-up actions.


• Improve alert quality, anomaly detection, escalation processes, and shared operational tooling in collaboration with infrastructure teams.


• Lead reliability assessments for high-risk changes and new services, covering production readiness, capacity, failure modes, rollback strategies, and operational risks.


• Introduce deliberate failure testing, game days, and chaos exercises to identify weaknesses and validate safe operational limits before incidents occur.


• Work directly with engineering teams on complex reliability challenges through focused engagements, leaving behind stronger practices and clear ownership.


• Coach Staff and Lead engineers to become reliability advocates within their respective teams and help establish distributed SRE ownership.


• Develop lightweight, repeatable operational standards covering production readiness, on-call practices, runbooks, change safety, and service operability.


• Partner with architects and technical leads to ensure reliability and failure tolerance are incorporated into system design rather than addressed after deployment.


• Remain hands-on during production incidents and investigations, building tooling, dashboards, automation, and reference implementations where appropriate.


• Promote effective use of AI for incident investigation, telemetry analysis, postmortem development, runbook creation, observability, and reliability tooling.


• Help structure operational data, alerts, dashboards, and runbooks so that both engineers and AI agents can safely interpret and act on production signals.


• Contribute production fixes and improvements directly through code and infrastructure changes rather than limiting the role to recommendations and reviews.

• 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.


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


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


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


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


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


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


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


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


• 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.


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


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


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


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


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


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


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


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


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

• Fully remote working environment.


• Opportunity to become the first dedicated Site Reliability Engineer and establish organization-wide reliability practices.


• High level of autonomy and direct influence over engineering standards, operational practices, and platform reliability.


• Opportunity to work across multiple engineering teams and critical production systems.


• Close collaboration with engineering leadership, architects, infrastructure teams, and technical leads.


• Opportunity to shape AI-assisted reliability practices and the future of production operations.


• Strong focus on professional growth, technical leadership, coaching, and knowledge sharing.


• Inclusive, globally distributed engineering environment that values diverse perspectives and backgrounds.


• For US-based employees, the stated cash compensation range is $177,000–$240,000 USD, with actual offers varying according to factors such as experience, skills, education, certifications, and market conditions. Compensation may differ for other hiring locations.


• Remote work eligibility is subject to applicable regulatory and security requirements in the candidate's location.

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