Development Operations Engineer supporting enterprise application development in Java and/or C. Ensuring high availability and operational excellence in modern payment solutions.
About the role
- Site Reliability Engineer designing and supporting Kubernetes environments for F5's UDF platform. Collaborating with cross-functional teams to ensure reliability and operational excellence.
Responsibilities
- Design, deploy, and manage Kubernetes clusters and ensure efficient container orchestration
- Implement and maintain Kubernetes-based deployment pipelines
- Optimize resource allocation within Kubernetes clusters
- Develop and maintain high-availability and fault-tolerant Kubernetes architectures
- Design and implement observability pipelines for real-time monitoring of Kubernetes clusters
- Leverage tools such as Cloudwatch, DataDog, Grafana, or similar platforms
- Establish logging, tracing, and alerting strategies
- Automate infrastructure management tasks to support effective AI functionalities
- Support Infrastructure-as-Code (IaC) methodologies
- Collaborate with product teams and sales engineering to integrate F5 products into the UDF platform
Requirements
- Bachelor’s degree in Computer Science, Software Engineering, or a related technical field (or equivalent experience)
- 4+ years of experience in Site Reliability Engineering (SRE), DevOps, or similar roles
- Strong expertise in managing Kubernetes clusters and containerized workloads in production environments
- Hands-on experience deploying and managing Kubernetes environments in AWS, especially using EKS
- Proficient in monitoring and observability tools, including CloudWatch, Grafana, Fluentd, DataDog, or equivalent platforms
- Expertise with Infrastructure-as-Code (IaC) tools such as Terraform, Helm, or CloudFormation
- Solid understanding of networking, storage, and compute infrastructure within containerized environments
- Proficiency in coding and scripting languages, including Python, Go, or Bash
- Expertise in applying security best practices to Kubernetes environments
- Familiarity with GPU-based workloads in Kubernetes environments and optimization strategies for AI-based workloads
- Experience with orchestrating, troubleshooting, and optimizing complex network environments in AWS and GCP VPCs
- Experience working with hypervisors in GCP VPCs
Benefits
- Health insurance
- 401(k) matching
- Flexible work hours
- Paid time off
- Remote work options
- Professional development opportunities
- Bonus
- Stock options
- Equipment allowances
- Wellness programs
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