• Design, build, and maintain backend services and APIs that power Loris’s conversation intelligence platform. • Integrate machine learning models into production, ensuring they are reliable, performant, and easy to update. • Collaborate closely with product managers, designers, and data scientists to ship impactful, user-facing features. • Own the architecture, development, and maintenance of backend services that ingest and normalize data from external systems (e.g., Salesforce, Zendesk, Intercom, Five9). • Build resilient and scalable ETL/ELT pipelines for data ingestion and enrichment. • Stay current with API changes, rate limits, and other nuances of third-party platforms. • Write clean, maintainable code and participate in design reviews and architecture discussions. • Monitor production environments, debug complex issues, and drive performance improvements.

• Design, develop, and maintain back-end systems and services. • Collaborate with front-end developers, product managers, and other stakeholders to deliver high-quality software solutions. • Write clean, maintainable, and efficient code. • Optimize applications for maximum speed and scalability. • Ensure the security and integrity of applications. • Troubleshoot and debug issues as they arise. • Mentor and guide junior engineers, fostering a culture of learning and growth. (for seniors) • Stay up-to-date with the latest industry trends and technologies.

• Be a technical point of contact for various stakeholders • Be technically talented, able to contribute quality code • Responsible for the quality, scope, and timeliness of deliverables

• Deploy, manage, and upgrade Kubernetes clusters using tools like kubeadm, EKS, AKS, GKE, or Rancher. • Implement robust RBAC, network policies, ingress controllers, and security frameworks in Kubernetes. • Automate cluster provisioning and application deployment pipelines using Terraform, Helm, and ArgoCD. • Build reusable modules for consistent infrastructure delivery across staging and production. • Integrate Kubernetes with modern CI/CD workflows for rapid, safe application delivery. • Support GitOps practices and continuous deployment automation. • Implement observability for Kubernetes using Prometheus, Grafana, Loki, and Fluentd/Fluent Bit. • Troubleshoot performance issues, failed pods, memory leaks, and cluster degradation events. • Operate Kubernetes workloads across AWS, Azure, GCP, and hybrid/on-prem environments. • Use tools like Velero, Kasten, or Stash for backup/restore strategies in Kubernetes. • Partner with application developers, SREs, and security teams to implement best practices. • Serve as a technical advisor on cloud-native architectures and containerization.