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Site Reliability Engineer All potential candidates should read through the following details of this job with care before making an application. Hybrid (3 days onsite, 2 days remote) full‐time. No visa sponsorship.
Base pay: $150,000 – $155,000 per year, subject to skills and experience. A prestigious company seeks a Site Reliability Engineer focused on observation, logging, and capacity planning. The role requires experience with Linux, Kubernetes/Docker, Terraform, Jenkins, Ansible, Harness, and Kafka.
Responsibilities:
  • Collaborate with development, operations and infrastructure teams to ensure availability of services, and to work through implementation issues
  • Develop automation for incident response and to prevent problem recurrence
  • Create and enhance runbooks to respond to service outages or degradations
  • Assess the production readiness of services
  • Define and track operational metrics for production performance, reliability, scalability and availability
  • Architect, develop and maintain shared services and tools to improve reliability and reduce toil across the organization
Qualifications: Bachelor's or Master's Degrees in Computer Science, Information Systems or another related field, or equivalent work experience Minimum of 4+ years of experience in Site Reliability Engineering / DevOpsExperience with maintaining and troubleshooting large‐scale distributed systems Experience managing infrastructure in public cloud environments like AWS (preferred), Azure or GCPExperience with AIOps and predictive analysis for anomaly detection, forecasting system capacity using monitoring and alerting tools like Splunk, AppDynamics, Datadog, StackDriver, Sysdig, Prometheus or Grafana Programming/scripting experience in languages xmcpwfu like Java, Bash, Python or GoExperience with distributed messaging systems such as Kafka, RabbitMQ, or ActiveMQExperience with container orchestration systems such as Kubernetes, Mesos, Docker Swarm or Rancher Experience with CI/CD tools such as Jenkins, Travis, Harness, Appveyor, CodeBuild or Code PipelineFamiliarity with leveraging large language models (LLMs) to automate and optimize SRE workflows, including scripting, incident report summarization, or AI workload maintenance Seniority LevelMid‐Senior

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