Site Reliability Engineer

Engineering Group, Engineering Group > Software Engineering

Cloud Infrastructure & Infrastructure as Code

• Design, build, and manage cloud infrastructure with a primary focus on AWS, integrated with OpenStack environments
• Build and maintain Infrastructure as Code using:
  • Terraform
  • Ansible
  • Kubernetes (manifests / Helm)
• Design infrastructure solutions for:
  • Scalability
  • High availability
  • Performance
  • Reliability
  • Cost efficiency
• Implement redundancy, failover, and disaster‑recovery patterns across services and regions
• Perform capacity planning based on performance metrics, usage trends, and utilization data

• Operate and scale production Kubernetes clusters in large‑scale environments
• Partner with development and QA teams to:
  • Improve system reliability and resiliency
  • Automate scalability and availability mechanisms
• Apply SRE principles including:
  • Service reliability ownership
  • Proactive failure prevention
  • Continuous improvement of operational processes
• Support microservices‑based and distributed system architectures

• Manage and evolve CI/CD pipelines (e.g., Jenkins)
• Automate infrastructure provisioning, configuration, and lifecycle management
• Write, maintain, and improve runbooks for operational processes
• Build automation to reduce manual intervention and operational toil
• Plan and execute infrastructure upgrades and maintenance activities
• Proactively identify and address technical and infrastructure debt

• Operate, tune, and scale data and streaming platforms, including:
  • Kafka, Zookeeper
  • NiFi
  • Elasticsearch
  • MySQL, Vertica
• Diagnose and resolve performance and stability issues across data pipelines
• Ensure data platform reliability, throughput, and resilience at scale

• Design and maintain knowledge‑driven automated runbooks and operational bots
• Develop AI‑assisted operational workflows, including:
  • Incident analysis and summarization
  • Intelligent diagnostics and remediation suggestions
  • Automation of repetitive operational decision‑making
• Work with LLM‑based agent frameworks (e.g., Claude Agent SDK or similar):
  • Integrate agents with logs, metrics, monitoring, and internal tools
  • Implement guard‑railed, controlled‑action automation for production use
• Research and propose new concepts, tools, and AI‑driven approaches to improve reliability and efficiency

• Design and operate monitoring and observability systems using:
  • Prometheus
  • Grafana
  • ELK stack
• Improve alert quality, signal‑to‑noise ratio, and troubleshooting efficiency
• Lead incident response activities, root cause analysis, and post‑incident reviews
• Support software engineers in debugging complex production issues across distributed systems
• Embed reliability, automation, and operational readiness into system design

• Extensive experience operating large‑scale distributed cloud systems
• Hands‑on experience with AWS in production environments
• Direct experience working with OpenStack
• Strong Linux background in large‑scale SaaS or production systems
• Ability to:
  • Maintain and improve existing mission‑critical systems
  • Prioritize and systematically reduce technical and infrastructure debt
• Strong understanding of designing for operational excellence, not just greenfield solutions

• Programming: Strong experience with Python and/or Go
• Cloud & IaC: Terraform, Ansible, CloudFormation or equivalent
• Containers: Kubernetes (production experience)
• CI/CD: Jenkins and modern CI/CD practices
• Data & Streaming: Kafka, NiFi, Elasticsearch, MySQL, Vertica, Zookeeper
• Observability: Prometheus, Grafana, ELK
• Infrastructure: Nginx, Linux internals
• AI / Automation (advantage):
  • Experience integrating AI or LLMs into operational workflows
  • Familiarity with agent‑based automation concepts

3+ years in:

• overall experience managing infrastructure
• Linux administration in large‑scale environments
• operating production systems on AWS and/or OpenStack
• managing Ku