Kenneth Chung

Staff Software Engineer at Stripe

Led the design, development, and horizontal scaling of Stripe’s card platform, supporting expense management, payouts, and embedded finance for enterprise customers. Built high-throughput authorization and funding services using Go and Java (Spring Boot), with gRPC, Kubernetes, Docker, on AWS (EC2, RDS, Lambda, S3, IAM), enhancing processing efficiency and reliability. Designed REST and GraphQL APIs with OAuth and JWT, enforcing rate limiting, schema validation, and contract testing, and delivered end-to-end SDKs in TypeScript, Python, and Java. Architected a real-time card controls engine (MCC restrictions, velocity limits, merchant-locked cards, and just-in-time funding) using Kafka and Redis. Developed ML pipelines for fraud detection and risk scoring (TensorFlow, PyTorch) and integrated inference into real-time payment flows, reducing false positives and chargebacks. Integrated OpenAI APIs to build an AI-powered internal assistant (TypeScript, Node.js, React), boosting engineerin

Software Engineer at Rescale

Designed and built the core orchestration engine for ScaleX Enterprise using Python (Flask, Celery, Redis) and Go, scaling to 100,000+ CPU cores and 5,000+ concurrent simulation jobs across on-premise clusters and AWS, Azure, and GCP.

Software Engineer at Escale

Designed and built the core orchestration engine for Scale X Enterprise using Python (Flask, Celery, Redis) and Go, scaling to 100,000+ CPU cores and 5,000+ concurrent simulation jobs across on-prem clusters and AWS, Azure, and GCP. Developed a high-performance job scheduler and resource manager in Go, replacing early Python implementations and enabling scalable, low-latency workloads. Implemented secure multi-party file staging and a client-side encryption gateway with Node.js and TypeScript, enabling chunked, resumable uploads with AES-256-GCM for ITAR/EAR-regulated workloads. Contributed to migrating critical systems from Python 2 to Python 3 and introduced Go-based microservices for latency-sensitive components, including GPU allocation, high-speed network fabric management, and health checks.