Coupang is reimagining the shopping experience with the goal of wowing each customer from the instant they open the Coupang app to the moment an order is delivered to their door. Powered by an outstanding end-to-end e-commerce and logistics network and a fanatical culture of customer centricity, Coupang has broken tradeoffs around speed, selection and price. Today, we provide exceedingly fast shipping speeds on millions of items including fresh groceries, delivered within hours nationwide, 365 days a year. We are doing this for millions of consumers in Korea. Korea is home to one of the largest and fastest growing e-commerce opportunities anywhere in the world.
Coupang has been added into the 2023 fortune 500 list, a ranking U.S-based companies by revenue. We have been named as one of the ‘50 Smartest Companies in the World’ by MIT Technology Review, and as one of Forbes magazine’s ‘30 Global Game Changers.’ In 2020, we placed second on CNBC’s ‘Disruptor 50’ list.
Job Overview:
The AI Storage and Networking team builds and maintains the critical infrastructure that powers the data lifecycle for AI/ML workloads across the organization. Our mission is to deliver high-performance, scalable, and secure storage and networking solutions that enable seamless data access, movement, and management for AI applications.
We are seeking an experienced Staff Software Engineer to lead the design and development of robust systems that support intelligent data orchestration, high-throughput data transfer, and low-latency access across distributed environments. This role is pivotal in shaping the future of AI infrastructure, including services like data-sync service, vector databases, caching, and key-value stores
What You Will Do
As a Staff Software Engineer, you will partner with leaders of multiple platform teams. You will work closely with the product team to define and implement simple solutions of complex infrastructure problems while ensuring to build a highly scalable, reliable and efficient platform for our customers. You will technically guide teams working on full stack development teams using JAVA, Go, Kubernetes, Kubeflow, Argo CD and Rest. You will be accountable for hiring and developing technical leaders and top talent, raising the bar on engineering and operational excellence.
In this role, you will:
- Design and implement scalable microservices using Java Spring Boot, focusing on storage, data access, and networking for AI/ML workloads.
- Design and implement the development of a next-generation Data Sync Service, enabling efficient, secure, and policy-compliant data movement across hybrid environments.
- Build and maintain services such as vector databases, embedding generation APIs, caching layers, and key-value stores.
- Develop high-performance data caching and integration services to support distributed AI pipelines.
- Collaborate with AI platform teams to integrate storage and networking capabilities into model training and inference workflows.
- Ensure reliability, observability, and performance of backend systems through rigorous testing and monitoring.
- Mentor junior engineers and contribute to architectural decisions that shape the future of AI infrastructure.
- Collaborate with AI/ML platform teams to integrate storage and networking capabilities into model training, inference, and data preparation pipelines.
- Drive innovation in data accessibility, vectorization services, and metadata management to support AI/ML workflows at scale.
- Partner with product managers and cross-functional teams to define roadmaps for AI data infrastructure.
- Ensure operational excellence through observability, automation, and proactive incident management.
- Mentor and grow a team of engineers focused on distributed systems, storage, and networking.
Qualifications
- At least 10 years of experience in software engineering, with a focus on distributed systems, storage, or networking.
- Proficiency in Java is a must along with Go or Python.
- Hands-on experience with Kubernetes, Rest and cloud-native technologies (AWS, GCP, or Azure).
- Deep understanding of data movement tools and protocols.
- Familiarity with AI/ML infrastructure and data formats (e.g., embeddings, tensors).
- Experience with technologies like Redis, Milvus, Weaviate, Kafka, and object storage systems.
Preferred Qualifications
- Proven experience building and scaling backend systems for data-intensive applications.
- Deep expertise in Java Spring Boot, Hibernate, and RESTful API design.
- Understanding data governance, compliance, and access control in distributed systems.
- Familiarity with vector databases, embedding generation, and semantic search
- Experience with Kubernetes, Docker, and container orchestration in production environments.
- Strong understanding of networking protocols, data transfer optimization, and secure data handling.
- Hands-on experience with Redis, Memcached, or other caching technologies.
- Exposure to key-value stores like Redis, etcd or RocksDB for metadata and configuration management.
- Experience integrating with AI/ML frameworks or pipelines (e.g., TensorFlow, PyTorch, ONNX).
- Experience with observability tools (e.g., Prometheus, Grafana, ELK stack).
- Familiarity with cloud platforms (AWS, GCP, Azure) and cloud-native development practices.
- Ability to mentor engineers and contribute to architectural decisions in a collaborative environment.
