Backend and DevOps Engineer

Job Detail

Background Rida is an AI-powered logistics platform that helps businesses reduce operational costs and scale deliveries without owning fleets or managing internal dispatch teams. With a hybrid model of dedicated fleets and freelancers, all orchestrated by our AI, we enable highly customizable logistics at scale. Job scope Join us in shaping the future of logistics by building powerful backend systems and robust infrastructure that power real-time AI-driven delivery optimization. As our DevOps & Backend Software Engineer, you’ll architect and scale core backend services, create deployment pipelines, and ensure our systems remain reliable under dynamic, high-throughput workloads. You’ll be pivotal in bridging software engineering with infrastructure, enabling our AI models and operational platforms to thrive in production. Key Responsibilities: Scalable Backend Architecture & Development Design, build, and maintain scalable, modular backend services using Node.js and Python to support our web, mobile, and internal platforms. Develop secure, high-performance RESTful and GraphQL APIs, with best practices in authentication, rate limiting, and load handling. Infrastructure Architecture & Deployment Architect cloud-native infrastructure to support AI model training, deployment, and continuous delivery. Use Docker, Kubernetes, and infrastructure-as-code tools to build robust, modular environments. Model Serving & GPU Workload Management Develop scalable endpoints and backend systems for real-time and batch AI model inference, including model versioning, A/B testing, and rollback mechanisms. Manage cloud compute and GPU with autoscaling and cost optimization on AWS/GCP/Azure. Observability & Reliability Engineering Implement monitoring and alerting systems (Prometheus, Grafana, ELK, OpenTelemetry) to ensure high availability and rapid diagnostics across models and APIs. Design health checks, logging pipelines, and automated incident diagnostics. Testing & Quality Assurance Write and maintain unit, integration, and end-to-end tests using Jest, PyTest, Postman, or similar frameworks to guarantee code quality and system stability. Process Optimization & Automation Build CI/CD pipelines that automate testing, containerization, and deployments, reducing manual overhead and accelerating release cycles.