AI Engineering
Core
Develop large-scale, highly available AI cloud services, managed Kubernetes services with GPU-native orchestration, and enterprise AI agent platforms.
Role type
Senior IC cloud platform and AI infrastructure engineer
Builds
GPU virtual machines, bare-metal services, container services, networking, storage, billing, monitoring, security, multi-region resource management, managed Kubernetes, distributed training, model fine-tuning, inference acceleration, serverless inference, model APIs, evaluation systems, model-serving capabilities, and AI agent platforms
Domain
Cloud infrastructure, AI/ML operations, GPU computing, distributed systems
Deliverable
production ML models
Required skills
Go, Python, C++, Java, Rust, Kubernetes, Docker, Helm, Terraform, OpenStack, Prometheus, Grafana, Argo, Istio, PostgreSQL, Redis, message queues, distributed storage
Preferred skills
Experience developing or operating large-scale cloud, Kubernetes, AI training, inference, or agent platforms
Technologies
GPU virtual machines, bare-metal services, container services, networking, storage, billing, monitoring, security, multi-region resource management, distributed training, model fine-tuning, inference acceleration, serverless inference, model APIs, evaluation systems, model-serving capabilities, AI agent platforms, workflow orchestration, retrieval-augmented generation, memory, sandbox execution, multi-agent collaboration
Responsibilities
Develop large-scale AI cloud services; Build managed Kubernetes services with GPU-native orchestration; Develop distributed training and model deployment systems; Build enterprise AI agent platforms; Work on GPU scheduling and distributed systems; Join Cloud Platform Engineering, AI Operations/MLOps/Site Reliability Engineering, MaaS and model-serving infrastructure, AI Agent and Application Engineering, or AI Research based on assessment
Seniority
Early-career (2027 fresh graduate or up to 2 years experience)
