Stephen Prater
Member Of Technical Staff at OpenAI
Portland, Oregon, United States
Summary
🤩
Rockstar🎓
Top SchoolStephen Prater is a seasoned full-stack engineer and technical leader with 15 years of experience building scalable systems, AI products, and high-performance search infrastructure. Based in Portland, he has led engineering organizations and hands-on delivery at Shopify—where his patented AI techniques helped cut support costs by $30M/year—and now contributes to AI work at OpenAI. He combines deep systems and backend expertise (notably improving Elasticsearch performance and contributing DSL enhancements to elastic/elasticsearch-ruby) with practical product impact, having slashed latency and hosting costs across multiple platforms. A mentor to large engineering teams and a pragmatic open-source contributor, he has a track record of turning maintenance headaches into high-velocity teams and measurable savings. Less obvious: he pairs that systems rigor with a playful engineering bent—“making large, murderous robots” hints at a taste for ambitious, hands-on projects that bridge hardware thinking and software scale.
15 years of coding experience
20 years of employment as a software developer
Bachelor's degree, Bachelor's degree at University of Central Arkansas
Stackoverflow
2,450reputation
220kreached
26answers
3questions
shell
top-5%
vim
top-5%
Github Skills (30)
clientside10
dsl10
amazon-elasticsearch10
test-runner10
taskfile10
searching10
ruby10
elasticsearchquery10
go10
aws-elasticsearch10
tasker10
elasticsearch10
build-tools10
webclient10
runner10
Programming languages (20)
Github contributions (5)
go-task/task
May 2019 - Aug 2019
A task runner / simpler Make alternative written in Go
Role in this project:
Backend Developer
Backend DeveloperContributions:13 commits, 2 PRs, 18 comments in 3 months
Contributions summary:Stephen primarily contributed to the implementation of preconditions within the `go-task/task` repository, a task runner written in Go. They added new functionalities to the `task` tool, specifically focusing on the implementation of preconditions. The user also modified the codebase, including core files like `task.go`, `precondition.go`, and relevant test files, while also adjusting the versioning to support new features. These changes involved expanding the capabilities and improving the error handling of the tool.
golangtaskfiledevopsgotask-runner
elastic/elasticsearch-ruby
May 2016 - Feb 2017
Ruby integrations for Elasticsearch
Role in this project:Back-end Developer
Back-end DeveloperContributions:5 commits, 4 PRs, 12 comments in 9 months
Contributions summary:Stephen primarily contributed to the Elasticsearch DSL (Domain-Specific Language) implementation in Ruby. They focused on enhancing the DSL's functionality, including allowing context access in search blocks and correctly implementing the `Sort#empty?` method. Furthermore, the user refactored aggregations into a dedicated class and added the ability to configure the `keyed` option for the "Range" aggregation, indicating a focus on improving and extending the library's features.
elasticrubyrubynlpintegrationselasticsearch
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