Special Skills Advanced Observability ability: Ability to design end-to-end observability stacks (metrics, logs, traces) and diagnose complex distributed system issues. AI-Ops Proficiency: Hands-on experience with AI-driven monitoring, anomaly detection, and predictive analytics. Automation Mastery: Strong skills in automating reliability workflows, including self-healing scripts, automated rollbacks, and infrastructure-as-code. Cloud Native Reliability: Deep familiarity with Kubernetes, service mesh technologies, autoscaling strategies, and resilient microservices design. Chaos Engineering: Ability to design and execute controlled failure scenarios to validate system robustness. Performance Engineering: Skilled in identifying bottlenecks, optimizing workloads, and tuning cloud/edge environments. Incident Command: Strong capability to lead incident response, root-cause analysis, and post-mortem improvements. Scalable Architecture Understanding: Ability to build systems that handle peak loads, fail gracefully, and recover instantly. Security-Aware Engineering: Knowledge of secure configurations, zero-trust principles, and compliance-aligned reliability. Scripting & Automation Languages: Strong command of Python, Bash, Go, or similar languages for tooling and automation.