Cloud Engineer – Observability SRE

Cloud Engineer Observability SRE Location: Hybrid in San Francisco, CA12 Months USC only Pay Rate: $60-65/hr. on C2C Job Description: 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:o OpenSearch/ELK,o Prometheus,o Grafana,o Splunk, ando 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 SkillsGeneral Abilities· Bachelor’s degree in computer science or related fieldGeneral 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:o Triaging alertso Leading incident responseo Writing post-incident reviewso 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:o Helm chart managemento Pod schedulingo Resource tuningo 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:o OpenSearch/Elasticsearcho Prometheus/Mimiro Grafanao Lokio Splunko LogstashDesired Skills· Apache Kafka/AWS MSK: Experience in at least one (³1) of the following:o Operating or tuning Kafka clusters at scaleo 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:o Forwarder management,o Search optimization,o Index lifecycle, and/oro 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):o Government or industry security certification standards; examples:§ FedRAMP§ STIG§ IL5§ ISO 27001§ SOC 2o Container image hardening practiceso 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:o Accelerate engineering workflows,o Automate runbooks, and/oro Assist with incident triage· Deployment pipelines (Argo CD/Helm bundles): Experience with at least one (³1) of the following across multi-region clusters:o GitOps-style deployment workflowso Argo CD application managemento Helm bundle patternso 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:o Right-sizing cloud resourceso Analyzing spending across AWS serviceso Optimizing data retention policies (ISM/ILM)o Reducing storage costs