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Staff Site Reliability Engineer – Confluent Cloud Infrastructure

IBM · Bengaluru

CompanyIBM
RoleStaff Site Reliability Engineer – Confluent Cloud Infrastructure
LocationBengaluru
Work modeRemote
Experience6+ years
Job typeFull-time

About this job

IBM is hiring a Staff Site Reliability Engineer for Confluent Cloud, the managed Kafka streaming platform that runs across AWS, GCP and Azure. The role is remote within India and sits in a horizontal team responsible for the reliability standards and tools every engineering team uses.

About three quarters of the work is hands-on reliability engineering: automation, tooling, failure-pattern analysis and SLO frameworks. The rest is running the incident management program, acting as incident commander and coaching teams through post-mortems.

Eligibility

  • 10+ years of experience across SRE, incident management or reliability work
  • Hands-on cloud work on AWS, GCP or Azure
  • Deep experience with incident tooling such as Rootly or PagerDuty
  • Strong understanding of distributed systems; Kafka knowledge preferred
  • Deep observability, Kubernetes and CI/CD knowledge

Skills required

Site Reliability EngineeringIncident ManagementSLOs & Error BudgetsKafkaKubernetesAWS / GCP / AzureObservabilityPagerDutyRootly

What you will do

  • Find systemic failure patterns and design fixes that stop repeats
  • Define SLO/SLA frameworks and use error budgets to guide investment
  • Build automation and dashboards that cut incident toil
  • Serve as on-call incident commander and run incident training
  • Review customer-facing root cause documents for accuracy and clarity

How to apply

  • Open the official IBM job page with the Apply button and submit your application there.
  • Tailor your resume to incidents you commanded, reliability programs you led and the tooling you built.

Before the interview, prepare:

  • SLOs and error budgets: define an SLO for a streaming service and how you would use it
  • Incident command: roles, communication and running a large incident
  • Kafka failure modes: broker loss, under-replicated partitions and consumer lag
  • Post-mortems: writing a blameless review with actionable follow-ups

Apply on official website →

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Posted 30 Oct 2026 · Last checked 11 Nov 2026 · Official source

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