- Lead the architectural design, evolution, and scaling of distributed backend microservices and machine learning platforms.
- Establish, champion, and enforce engineering best practices across the organization, including rigorous code reviews, automated testing, design docs, and security protocols.
- Mentor and coach senior engineers, fostering a culture of technical curiosity, continuous learning, and high execution velocity.
- Design and implement high-performance, resilient, and secure cloud-native solutions using Python and modern web application frameworks.
- Drive the containerization and orchestration strategy using Docker and Kubernetes to ensure seamless deployments and efficient resource utilization.
- Build and maintain robust MLOps infrastructure to streamline the entire ML lifecycle.
- Own and secure AWS cloud infrastructure, optimizing networking setups including VPCs, DNS, ingress controllers, and service meshes.
- Architect end-to-end CI/CD pipelines and DevOps automation to facilitate reliable, friction-free daily deployments.
- Cultivate system visibility by implementing comprehensive observability stacks including Datadog, Prometheus, Grafana, and ELK.
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