Staff Software Engineer

Experience designing, building, and operating large-scale distributed systems in cloud environments.

Experience with AWS, Azure, or GCP, and cloud-native development practices.

Strong expertise in distributed systems technologies including Kafka, Cassandra, ClickHouse, MongoDB, or similar platforms.

Experience with Kubernetes, Docker, gRPC, Spring, and microservices architecture.

Experience building infrastructure, tooling, or platforms supporting machine learning and AI workloads.

Experience integrating with AI/ML frameworks or pipelines (e.g., TensorFlow, PyTorch, ONNX).

Our compensation reflects the cost of living across several US geographic markets. At Coupang, your base pay is one part of your total compensation.

The base pay for this position ranges from $152,000/year in our lowest geographic market to $282,000/year in our highest geographic market. Pay is based on several factors including market location and may vary depending on job-related knowledge, skills, and experience.

Medical/Dental/Vision/Life, AD&D insurance

Flexible Spending Accounts (FSA) & Health Savings Account (HSA)

Long-term/Short-term Disability

The Resource Fabric Engineering team builds and operates the foundational infrastructure and developer tools that power the AI lifecycle across Coupang.

Our mission is to provide scalable, reliable, and intelligent platforms that enable teams to efficiently build, deploy, and manage AI workloads.

We develop core services including resource management, workflow orchestration, model lifecycle tooling, and observability solutions that support machine learning innovation at scale.

We are looking for a Staff Software Engineer to lead the design and evolution of large-scale distributed systems and drive technical excellence across the platform.

Design and implement the development of a next-generation Resource Manager and AI developer tools, enabling efficient, secure, and policy-compliant data access across hybrid environments.

Lead the design of scalable, event-driven microservices for optimized resource management.