Backend Engineer

• Design, build, and maintain cloud-native backend services in Rust that support AI model deployment, inference, lifecycle management, and monitoring.
• Develop robust APIs and orchestration components to manage deployment workflows.
• Architect low-latency, high-throughput inference services optimized for real-time AI applications running in the cloud.
• Integrate backend systems with model registries, data processing pipelines, and monitoring tools to provide a seamless end-to-end AI lifecycle.
• Collaborate closely with AI researchers, DevOps, and hardware teams to co-design scalable deployment pipelines tailored for cloud environments.
• Implement observability and telemetry systems to monitor model performance, availability, and cost efficiency.
• Work with both SQL and NoSQL databases to manage model metadata, logs, and large-scale inference results.
• Deploy, scale, and operate workloads on Kubernetes, ensuring high reliability, elasticity, and performance across cloud environments.
• Continuously evaluate and adopt new technologies in Rust, backend systems, and AI infrastructure to keep the platform state-of-the-art.

Rust Backend Engineer – AI Platform

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Staff Backend Engineer