Bachelor's degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience)
8+ years of experience in Production Engineering, SRE, or large-scale infrastructure operations
Demonstrated experience supporting GPU workloads, HPC environments, or latency/throughput-sensitive distributed systems
Previous experience in Infrastructure roles building or managing compute, storage or networking platforms
Deep knowledge of Linux/Unix systems, including debugging complex issues across kernel and user space
Strong understanding of modern cloud infrastructure fundamentals including Kubernetes, distributed systems, virtualization, and cloud platforms (AWS/GCP)
Proven track record with incident management practices and reliability frameworks (SRE, ITIL, or similar)
Hands-on experience with monitoring and observability tools such as Prometheus and Grafana
Experience with infrastructure-as-code and configuration management tools such as Terraform or Ansible
Proficiency in scripting or programming with languages such as Go, Python, C, or C++
Exceptional communication skills and the ability to influence and collaborate across engineering teams
Ability to remain calm and effective while troubleshooting complex issues in high-impact production environments
A growth mindset and strong commitment to reliability engineering, automation, and operational excellence
Experience leading Kubernetes or container orchestration platforms at scale
Exposure to change management processes, operational readiness reviews, or structured root cause analysis
Experience designing self-healing systems, automated remediation, or event-driven operational tooling
Interest in scaling AI or HPC infrastructure and solving reliability challenges in GPU-heavy environments
Passion for mentorship, growing teams, and developing deep expertise in Production Engineering