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We're not just building better tech. We're rewriting how data moves and what the world can do with it. With Confluent, data doesn't sit still. Our platform puts information in motion, streaming in near real-time so companies can react faster, build smarter, and deliver experiences as dynamic as the world around them. It takes a certain kind of person to join this team. Those who ask hard questions, give honest feedback, and show up for each other. No egos, no solo acts. Just smart, curious humans pushing toward something bigger, together. One Confluent. One Team. One Data Streaming Platform.
Job Responsibility
Analyze systemic failure patterns and design improvements that prevent incident recurrence
Define and maintain SLO/SLA frameworks
use error budgets to guide reliability investments
Build tooling and automation to reduce incident response toil and scale team impact
Own Rootly configuration, workflows, and integrations with PagerDuty, Jira, Confluence, and Slack
Analyze reliability data to identify systemic improvements
build dashboards that drive action
Explore AI-assisted approaches to documentation quality and incident analysis
Design scalable reliability standards that reduce reactive workload over time
Own standards, practices, and continuous improvement of incident response
Serve as an on-call Incident Commander for production incidents, including acting as escalation IC when incidents exceed a team's management chain
Develop and deliver training programs for engineering teams at all levels
Coach teams through post-mortems and on developing actionable corrective actions
Edit and review customer-facing incident documents to ensure quality and clarity
Drive turnaround SLAs while maintaining technical accuracy
Ensure clear explanation of what happened, why, and how we'll prevent recurrence
Partner with engineering leaders to elevate reliability practices
Be the expert who teams proactively engage for guidance
Requirements
10+ years in SRE, incident management, or reliability engineering
Cloud experience with at least one of AWS, GCP, or Azure
Deep expertise with incident management tooling (Rootly, PagerDuty, or similar platforms)
Strong understanding of distributed systems and failure modes at scale—Kafka/event streaming expertise preferred, or demonstrated rapid mastery of complex systems
Deep experience with observability: metrics, logging, tracing—ability to diagnose complex issues
Kubernetes and container orchestration experience
Understanding of CI/CD pipelines and release processes
Systems thinking: understanding how infrastructure design choices affect failure modes and recovery
Familiarity with SLO/SLA frameworks
Track record as a trusted advisor across engineering organizations
Experience driving org-wide process and cultural changes
Strong written communication (design docs, one-pagers, runbooks)
Post-mortem facilitation experience
Experience with async collaboration across time zones
Large company experience navigating reliability/incident programs at 500+ engineer organizations
Nice to have
Multi-cloud experience (minimum 2+ of AWS/GCP/Azure)
Modern CI/CD, GitHub, AI-assisted workflows—you'll have the freedom to build what you need