• Designed and led implementation for a scalable data ingestion engine using AWS Lambda, AWS S3, and AWS SNS

• Architected and built a production-ready trustworthy LLM implementation capable of serving hundreds of requests per second

• Championed multiple observability initiatives, including session tracking, log aggregation,real-time alerting, and APM with industry standard tools such as Datadog and OpsGenie

• Developed a job scheduler to allow for reliable execution of synchronous and asynchronous real-time tasks using Python

• Implemented dynamic and performant Python dataclass serialization using a custom just-in-time Protobuf compiler

• Built a hierarchical agent framework to enable behavior trees for reinforcement learning agents

• Developed tools and infrastructure to facilitate the safe execution and oversight of trading systems using Python

• Interfaced with 3rd party APIs (such as Slack) to provide convenient alerting of issues in production systems

• Created Django views to display server metrics across multiple data centers to allow for easier monitoring of system health