Infrastructure Engineer (SRE + AIOps)

Position Summary As an Infrastructure Engineer (SRE + AIOps), you will keep AIQ’s video-analytics platform reliable, observable, and self-healing across cloud and edge deployments. You will build the Kubernetes-based delivery tooling, observability stack, and AIOps-driven monitoring that let the platform scale safely and recover quickly when things go wrong. Responsibilities • Own site reliability engineering (SRE) for AIQ’s cloud and edge distributed systems, ensuring availability, scalability, and resilience. • Build and maintain Kubernetes (k3s) clusters, Helm charts, and ArgoCD pipelines for CI/CD and marketplace-style deployments. • Develop automation and platform tooling using Python (FastAPI), Go, or Node.js. • Implement and maintain the observability stack — Prometheus, Grafana, OpenTelemetry, and ELK / OpenSearch — for metrics, logs, and traces. • Apply AIOps techniques, including anomaly detection, alert correlation, and predictive incident management, to reduce alert noise and surface issues early. • Build event-driven pipelines using Kafka / RabbitMQ for scalable data and telemetry flows. • Define and maintain Infrastructure as Code (Terraform, Helm, GitOps workflows) for repeatable, auditable deployments. • Drive reliability engineering practices — SLOs / SLIs, incident response, postmortems, and self-healing systems. Qualifications • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. • 4 – 8 years of experience in Site Reliability Engineering, DevOps, or Platform Engineering roles. • Hands-on experience with Kubernetes (k3s), Helm, and ArgoCD for CI/CD and marketplace-style deployments. • Proficiency in Python (FastAPI), Go, or Node.js for automation and platform tooling. • Experience with observability tooling such as Prometheus, Grafana, OpenTelemetry, and ELK / OpenSearch. • Familiarity with AIOps concepts, including anomaly detection, alert correlation, and predictive incident management. • Experience with event-driven systems (Kafka / RabbitMQ) and Infrastructure as Code (Terraform, Helm, GitOps workflows). • Strong grounding in reliability engineering practices: SLOs / SLIs, incident response, postmortems, and self-healing systems.