•Led the development of multiple critical path projects for leading fair chance background checks company driving $690 million of annual revenue using Ruby on Rails, Sinatra, Python, Go, Snowflake, Kafka, Datadog, and Kubernetes
•Worked with engineer teams to guide and enable systematic modularization of monolith codebase(650K LOC)
•Worked on project to systematically upgrade monolith codebase(650K LOC) from ruby 2.6 to 3.1 and rails 5 to 7
•Worked with 20 engineer teams and infra team to facilitate e2e microservice connections for cloned sandbox environment
•Tech lead for onboarding new criminal search vendors e2e from API testing and documentation, to code integration, to audit testing of vendor quality. Also developed and documented the onboarding process for repeatability with future vendors
•Led project to onboard 6 microservices owned by team to Okteto, a kubernetes based dev environment platform
•Tech lead for development of comprehensive system for detection, triage and resolution of stuck background check reports that resulted in a 30% reduction of total stuck report count
•Owned development of improved deep learning language model for criminal charge categorization by adding new features to model using fastai library and AWS Sagemaker
•Owned data analysis and code development of major cost savings features with estimated annual savings of $300K
•Mentorship role for several new engineers
