Shea Winkler
Principal Engineer at Private Memory Corp LLC
Denver, Colorado, United States
Summary
👤
Senior🎓
Top SchoolShea Winkler is a Principal Engineer based in Denver with nine years building distributed systems, data platforms, and AI infrastructure across public sector and agriculture. He has led end-to-end cloud data architectures—ETL, event-driven ingestion, BigQuery/Postgres warehousing, and Kubernetes deployments—delivering measurable ROI from proof-of-concept to production. His background in environmental and water science combined with an MS in Computer Science gives him a rare ability to translate scientific modeling needs into scalable, automated pipelines and user-friendly tooling. Shea has driven cross-organizational projects, managed teams, and integrated geospatial, satellite, and smart-contract/crypto concepts into data workflows. Currently advancing AI context and memory expansion at Private Memory Corp, he blends research curiosity with production rigor to solve complex data and modeling problems.
9 years of coding experience
8 years of employment as a software developer
B.S. Environmental & Energy Economics B.S. Environmental Restoration Science Energy Science Water Science, B.S. Environmental & Energy Economics B.S. Environmental Restoration Science Energy Science Water Science at University of Nebraska-Lincoln
English
Stackoverflow
1reputation
0reached
1answer
0questions
Github Skills (25)
homebrew10
ai10
cli10
retrieval9
ai-agent9
gemini9
rust8
agent-framework8
golang7
python6
pandas6
matrix5
cryptography4
encryption4
telegram-bot3
Programming languages (5)
Github contributions (5)
sheawinkler/hermes-agent-ultra
Apr 2026 - Jul 2026
Hermes Agent Ultra (built from hermes-agent-rs core by lumioresearch, @oxterrybit). Hermes-agent feature parity at commit level. Rust Performance
Contributions:1 release, 74 PRs, 283 pushes in 2 months
rusthermeshermes-agenthermes-agent-rust
sheawinkler/ContextLattice
Feb 2026 - Jul 2026
The local-first intelligence layer that gives AI agents durable continuity, explainable retrieval, portable context, and verified learning across harnesses.
Contributions:7 releases, 78 PRs, 178 pushes in 4 months
ai-agentagent-frameworkagent-orchestrationai-infracontext-engineering
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