Control Plane Architecture: Engineered a high-throughput Control Plane for LLM fine-tuning (Anthropic Claude 3 Haiku), utilizing Java and Kubernetes to orchestrate complex training lifecycles across thousands of nodes.
GPU Orchestration & Reliability: Architected a highly scalable platform for GPU compute management; developed custom health-check and session monitoring tools to ensure 99.9% uptime for long-running training jobs.
Observability & Throughput: Built comprehensive observability stacks for GPU workloads using internal AWS telemetry, identifying bottlenecks that led to a 25% increase in compute efficiency.
Production Optimization: Developed a high-performance model-loading mechanism to streamline the transition of fine-tuned weights into Amazon Bedrock production environments, significantly reducing Time-to-First-Token (TTFT).
Technical Leadership: Mentored 4+ SDEs on distributed systems patterns and fault-tolerant design, resulting in a more resilient GPU utilization pipeline and improved team velocity.
Business Impact: Directly enabled multi-million dollar revenue streams by delivering customized Anthropic model fine-tuning solutions for strategic enterprise clients like SK Telecom (SKT).
