Scalable AI/ML Cloud Infrastructure Optimization with GitOps and Observability Tools

As a rapidly growing AI/ML scale-up, we are experiencing increasing demand for our advanced machine learning solutions. To cater to this demand and maintain competitive advantage, we need to optimize our cloud infrastructure for scalability, reliability, and security. This project will involve implementing GitOps practices to streamline our deployment processes and manage our infrastructure as code using Terraform. We aim to leverage Kubernetes for container orchestration, ensuring seamless scalability across different cloud providers in a multi-cloud environment. Additionally, we are keen to integrate advanced observability tools such as Prometheus and Grafana for real-time monitoring and alerting. Security automation will be another critical aspect, aligning with industry standards to protect sensitive data and maintain compliance. Finally, we seek to incorporate CI/CD pipelines with Jenkins and ArgoCD to enhance our software delivery capabilities. The consultant will work closely with our in-house DevOps and engineering teams over 8-12 weeks to achieve these goals, ensuring our AI/ML services are robust, efficient, and secure.