• Design, implement, and manage highly available infrastructure for our cloud-based platforms (AWS). • Work with our internal engineering teams to architect and support AI/ML infrastructure, specifically managing AWS Lambda infrastructure, and some legacy SageMaker environments for model training, hosting, and inference. • Create and automate robust deployment pipelines using CI/CD tools (GitLab / GitHub Actions) for both web applications and machine learning models. • Build, maintain, and scale containerized applications with Docker and ECS/Fargate. • Implement MLOps best practices to streamline the transition of models from development to production. • Ensure system scalability and reliability through proactive monitoring, logging, and automated alerting. • Collaborate with both Product Engineers and Data Scientists to optimize performance, security, and infrastructure costs. • Manage and evolve our Infrastructure as Code (IaC) footprint.