Responsibilities

About the Team The Traffic Infrastructure team leverages unified platform capabilities to manage global edge infrastructure (China & Non-China), both self-built and third-party, providing standardized, compliant, scalable, and cost-effective traffic infrastructure capabilities for edge services. Our vision is to build a global edge traffic infrastructure platform and become the long-term cornerstone of ByteDance’s global edge business in terms of scale, performance, and cost. The Platform Engineering team is a comprehensive business building team. We focus on the operational efficiency of core workflows within the GTI business system, continuously evaluating the system's operational performance from perspectives including business modeling and collaboration processes. By leveraging modern engineering practices, we drive the GTI business system to operate automatically, efficiently, and stably, thereby enhancing customer experience. Our core focus areas include: 1. Customer Requirements & Product Delivery : Collaborate with product teams to optimize user experience and fulfill customer functional and resource requirements; deliver product capabilities that meet customer expectations, optimize product inventory turnover efficiency, and drive efficient resource delivery. 2. Resource Operations & Cost Optimization : Collaborate with the operations system to improve resource pool management efficiency, advance system automation, platformization, and datafication; monitor resource input-output efficiency to support continuous improvement of operational capabilities. Job Summary Join ByteDance’s Global Traffic Infrastructure (GTI) team to build and scale the edge cloud and global traffic platform that powers TikTok’s worldwide service delivery. You will focus on edge resource orchestration, traffic scheduling, cloud resource governance, and platform automation, ensuring high scalability, cost efficiency, and global service stability for billions of users. Responsibilities 1. Lead core R&D and architecture iteration of the company's traffic infrastructure platform, covering underlying modules including business governance, orchestration & scheduling, and resource management, to support unified management and elastic delivery of global cloud resources. 2. Build a full-lifecycle resource operations management platform spanning resource planning, provisioning, sales, runtime, and billing. Continuously optimize resource utilization and delivery efficiency, drive cost optimization, and ensure business resource competitiveness and customer cost-effectiveness. 3. Refine core business pipelines, polish domain models and engineering workflows, and design secure, robust systems aligned with business requirements and architectural characteristics. 4. Own on-call incident troubleshooting, performance bottleneck resolution, and capacity planning to guarantee year-round high availability of the cloud platform and stable iteration of core business workloads.

Qualifications

Minimum Qualifications 1. Bachelor’s degree or above in Computer Science, Software Engineering, Networking, Communications, or related fields, with minimum 3 years of hands-on R&D experience in cloud platform, cloud-native, or edge infrastructure domains. 2. Solid computer science fundamentals, with deep mastery of Linux system internals, process/memory/network models, and core networking principles including TCP/IP, virtual networking, and load balancing. 3. Proficiency in at least one of Go/C++/Python, with proven experience in large-scale backend or infrastructure development. 4. In-depth expertise in Kubernetes core architecture and component principles, with a track record of large-scale cluster optimization. 5. Familiarity with mainstream virtualization and container technologies, including working knowledge of KVM/QEMU, Virtio, container isolation, and image management underlying mechanisms. 6. Hands-on experience with cloud-native observability stacks; practical exposure to Prometheus, Grafana, logging pipelines, and distributed tracing systems is highly preferred. 7. Strong architectural thinking and incident root-cause analysis capabilities, with the ability to independently own complex module design, technical problem-solving, and cross-team collaboration. Preferred Qualifications 1. Prior R&D experience in edge computing, edge cloud, or distributed computing scheduling platforms. 2. Sound understanding of cloud computing technology stack, including eBPF, Cilium, DPDK, and high-performance network forwarding fundamentals. 3. Relevant work experience in multi-cloud/hybrid cloud architecture, OpenStack, or cloud infrastructure cost and billing strategy design. 4. Domain knowledge and architectural understanding of audio/video, CDN, or streaming media systems.

Job Information