About the Job: The company, a leader in AI-powered cloud and digital infrastructure, is seeking a Senior Site Reliability Engineer to drive transformative technology solutions globally. This role is crucial for designing, implementing, and operating scalable, reliable, and secure infrastructure that supports large-scale AI and HPC workloads. As a Senior Site Reliability Engineer, you will work closely with engineering, product, and operations teams to build and maintain CI/CD pipelines, manage Kubernetes-based environments, and implement observability systems that ensure high availability and performance across globally distributed platforms.
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Your Key Responsibilities:
- CI/CD & Automation: Design, build, and maintain robust CI/CD pipelines using tools such as GitLab CI, Azure DevOps, and/or Jenkins for secure software delivery.
- Kubernetes Operations: Optimize and manage Kubernetes clusters to ensure performance and resilience.
- Infrastructure as Code: Develop and maintain infrastructure using Terraform, Helm, Ansible, or similar tools.
- Observability & Monitoring: Implement monitoring solutions using Prometheus, VictoriaMetrics, Grafana, and ELK/EFK.
- Incident Management: Lead root cause analysis (RCA) and implement continuous improvement for system reliability.
- Reliability Engineering: Define SRE best practices, including SLAs, SLOs, and error budgets.
- Logging & Alerting: Build logging, alerting, and tracing systems for proactive issue detection.
- Security & Compliance: Enforce security best practices across CI/CD pipelines and runtime environments.
- Collaboration: Work cross-functionally to align platform capabilities with business needs.
- Mentorship: Guide junior engineers and contribute to knowledge sharing across teams.
- On-call Support: Participate in on-call rotations to support critical platform services.
Required Skills/Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
- 5+ years of experience in DevOps, Site Reliability Engineering, or platform engineering roles in production environments.
- Proven experience managing Kubernetes clusters (e.g., GKE, EKS, AKS, or self-managed).
- Hands-on experience with CI/CD tools and automation frameworks.
- Strong experience with infrastructure-as-code tools such as Terraform, Helm, or Ansible.
- Proficiency in container technologies (Docker, containerd) and orchestration with Kubernetes.
- Strong scripting/programming skills (e.g., Python, Bash, Go).
- Experience with observability and monitoring stacks (Prometheus, Grafana, ELK/EFK).
- Solid understanding of Linux systems, networking concepts, and cloud-native security best practices.
Preferred Skills/Qualifications:
- Experience supporting AI/ML or HPC workloads in production environments.
- Knowledge of GPU resource management, workload schedulers, and performance tuning.
- Familiarity with distributed systems and large-scale infrastructure environments.
- Experience with incident management frameworks and reliability engineering practices.
- Strong collaboration and communication skills across cross-functional teams.
