Senior Site Reliability Engineer, Chainlink Labs

• Demonstrated experience operating large-scale distributed systems and scalable data processing infrastructure in production, including managing availability, consistency, failure modes and performance trade-offs
• Operated Kafka or Kafka-compatible streaming platforms such as Redpanda in production, with hands-on experience in capacity planning, performance tuning and troubleshooting
• Provisioned and managed production infrastructure using Terraform, with version-controlled, reviewed and repeatable infrastructure changes
• Experience deploying, operating and troubleshooting production Kubernetes workloads, including resource management, scaling and safe rollouts

Desirable

• The Senior Site Reliability Engineer will own the reliability and operational performance of large-scale distributed systems and data infrastructure
• This role will strengthen the production operation of streaming and Kubernetes workloads while ensuring infrastructure changes are managed through repeatable, version-controlled practices
• The role will also improve the scalability and operational efficiency of the infrastructure that engineering teams depend on
• Enable critical product initiatives to launch on time. Deliver the streaming and data infrastructure required by CRE, CCIP, Data Feeds and Data Streams, translating product requirements into reliable Redpanda/Kafka and Flink capabilities
• Maintain 99.9% availability for critical data infrastructure as usage grows. Scale streaming and Kubernetes workloads, resolve throughput and recovery bottlenecks, and define SLIs that reflect the experience of consuming services
• Keep operational maintenance below 20% of team capacity. Reduce recurring incidents, manual interventions and routine maintenance through automation, actionable alerts, tested recovery procedures and repeatable vulnerability remediation
• Reduce cost to serve and make consumption accountable. Connect Redpanda topic traffic, Flink processing and BigQuery usage to the teams and services consuming them
• Increase infrastructure self-service and operational safety. Establish reusable infrastructure modules, deployment workflows and documentation that enable engineering teams to provision, test, scale and retire AWS and Kubernetes resources independently
• Use service adoption and consumer needs to guide infrastructure improvements. Establish visibility into infrastructure consumers, service adoption, reliability, cost and maintenance effort