Back-End Software Engineer, IBM Data and AI
Mar, 2018 - Present
Led initiative to create a standardized tool set for testing resiliency of IBM Cloud services
Coordinated with service teams to identify service steady state behaviors and possible chaos scenarios
Utilized both ChaosToolkit and internal tooling in Golang to execute network and resource utilization chaos on IBM Cloud/AWS/Azure Openshift clusters
Delivered pipelines for provisioning production instances of Netezza data warehouse PaaS/SaaS products
Automated configuration and provisioning of cloud infrastructure/Kubernetes clusters from various providers (AWS, Azure, IBM Cloud) through Bash/Python scripts, Helm charts, and Terraform
Extended automation to also support AWS GovCloud and air gapped environments
Engaged directly with customers to provide top tier support
Configured Linux-based systems for prototyping Db2 Warehouse on Openshift concept and wrote pytest suite for benchmarking/certifying container storage providers (ex. Portworx) on Db2 Warehouse
Developed Cloud Pak appliance dashboard components and hardware information REST API endpoints using React/Golang
Enabled Watson document insight service teams to systematically improve their models through structured evaluation of model output vs ground truth data
Implemented string alignment algorithms and bounding box techniques in Java/Scala for quantifying PDF-to-HTML conversion and NLP model performance in terms of precision, recall, and F1 scores
Delivered end-to-end microservice implementations of evaluation and feedback aggregation engines on Kubernetes with Spring Boot
Optimized service throughput with JMeter, VisualVM, and Flight Recorder to support evaluating large documents and thousands of pages per hour
Developed tooling in React to help model developers visualize legal element bounding boxes in PDFs and classification label errors