Cloud Engineer Observability SRE

About

The Grade 10 Cloud Engineer within the Customer’s Cloud Collaboration Technology Group will play a key role in building and operating scalable observability and infrastructure platforms supporting Webex microservices. This role requires strong hands-on expertise in Kubernetes, cloud infrastructure, and observability systems, along with the ability to operate independently and to own components end-to-end in production environments. Candidates will demonstrate extensive use of generative AI tools for code generation and production system troubleshooting.

Key Responsibilities

• Design, develop, and operate observability platforms - to perform logging, metrics, and/or tracing - for Webex microservices.
• Manage and optimize Kubernetes clusters across multi-region environments.
• Own CI/CD pipelines using Argo CD and Helm.
• Implement Infrastructure as code (IaC) using Terraform on AWS.
• Operate monitoring ecosystems, including but not limited to:
  • OpenSearch/ELK,
  • Prometheus,
  • Grafana,
  • Splunk, and
  • Kafka.
• Build automation to detect and remediate production issues.
• Ensure security compliance through vulnerability patching.
• Collaborate cross-functionally to improve reliability.
• Participate in on-call rotations and incident response.
• Contribute to distributed system design and operations.

Required Skills

General Abilities

• Bachelor’s degree in computer science or related field

General Technical Skills

• At least eight (³8) years of experience in a DevOps and/or SRE platform engineering role
• Incident response and on-call operations: Demonstrated experience in a 24/7 production environment, including but not limited to:
  • Triaging alerts
  • Leading incident response
  • Writing post-incident reviews
  • Maintaining SLA commitments across large-scale distributed systems
• IaC and automation: Proficiency with Terraform, Ansible, and/or equivalent IaC tooling for provisioning and managing cloud infrastructure at scale on AWS
• Scripting and development: Working proficiency in Python, Golang, and/or Bash for building automation scripts, operational tooling, and/or CI/CD pipeline integrations (e.g., Drone, GitHub Actions, Argo CD)

Specific Technical Skills

• Kubernetes and container orchestration: Production experience operating and troubleshooting workloads on Kubernetes at large scale (i.e., hundreds of deployments and thousands of pods), including but not limited to:
  • Helm chart management
  • Pod scheduling
  • Resource tuning
  • Multi-cluster operations
• Observability stack expertise: Hands-on experience - performing pipeline design, query optimization, and/or capacity planning for high-volume environments - in at least two (³2) of the following:
  • OpenSearch/Elasticsearch
  • Prometheus/Mimir
  • Grafana
  • Loki
  • Splunk
  • Logstash

Desired Skills

• Apache Kafka/AWS MSK: Experience in at least one (³1) of the following:
  • Operating or tuning Kafka clusters at scale
  • Managing the following across high-throughput streaming pipelines:
    • Topic configurations,
    • ACLs,
    • Consumer lag, and/or
    • Schema registries
• Splunk administration: Experience deploying, managing, and/or migrating Splunk Enterprise environments with Kubernetes-based log shipping architectures, including but not limited to:
  • Forwarder management,
  • Search optimization,
  • Index lifecycle, and/or
  • Integration
• OpenTelemetry and distributed tracing: Experience with deploying OpenTelemetry for data collection and application performance monitoring
• Security frameworks and container hardening: Familiarity with at least one (³1) of the following (for vulnerability remediation at scale):
  • Government or industry security certification standards; examples:
    • FedRAMP
    • STIG
    • IL5
    • ISO 27001
    • SOC 2
  • Container image hardening practices
  • Security scanning tools (e.g., Anchore, Grype)
• AI-augmented operations: Experience using LLMs, AI coding assistants, and/or custom AI agents (e.g., MCP servers, Copilot, Claude) to:
  • Accelerate engineering workflows,
  • Automate runbooks, and/or
  • Assist with incident triage
• Deployment pipelines (Argo CD/Helm bundles): Experience with at least one (³1) of the following across multi-region clusters:
  • GitOps-style deployment workflows
  • Argo CD application management
  • Helm bundle patterns
  • Blue/green or canary release strategies
• Cost optimization and capacity planning: Experience in at least one (³1) of the following in large-scale logging and/or metrics platforms:
  • Right-sizing cloud resources
  • Analyzing spending across AWS services
  • Optimizing data retention policies (ISM/ILM)
  • Reducing storage costs