AI Ops Engineer

- Implement AI-driven operations and automation using machine learning to streamline performance monitoring, workload management, and infrastructure operations - Create systems for anomaly detection to proactively identify and resolve system issues before they affect users - Develop automated root cause analysis through machine learning-driven event correlation - Establish predictive maintenance processes based on historical data and telemetry - Design and execute automation scripts for incident response - Build observability platforms to consolidate logs, metrics, and events into comprehensive dashboards - Implement advanced alerting mechanisms utilizing natural language processing and machine learning to enhance signal-to-noise ratio - Deploy Application Performance Management (APM) tools that are integrated with AI analytics - Ensure comprehensive visibility across cloud infrastructure, applications, and machine learning workloads - Design and sustain scalable AWS infrastructure utilizing CloudFormation, Terraform, or CDK - Manage containerized applications using Docker, ECS, Fargate, or EKS - Construct CI/CD pipelines that incorporate AI-driven deployment and quality assurance checks - Automate cloud operations to enhance cost-efficiency, scalability, and reliability - Confirm that all cloud architecture adheres to compliance requirements (FERPA, GDPR) - Collaborate with engineers and cross-functional teams to implement AIOps capabilities - Utilize Git-based workflows and engage in code reviews - Document operational processes, runbooks, and automation workflows - Continuously assess and adopt emerging AIOps tools and techniques - Contribute to fostering a culture centered on predictive and automated operations