About
Hi, I’m Nate. I build cloud data pipelines and the agentic systems that keep them running, and I write about what actually works when you put AI into production.
Currently, I’m a data platform engineer working on large-scale geospatial pipelines. Recent work: migrating a legacy ingestion system to AWS as a stack of flag-gated, backward-compatible PRs (test suite +70%), and an autonomous MCP-based processing system that cleared 50+ work units in a day at ~3x estimated throughput with a >90% no-action-needed detection rate.
Along the way I’ve root-caused silent schema-drift regressions that passed automated validation, built a data-quality tool that caught two live production bugs during its own demo prep, and led adoption of a standardized data-contract format across teams. I always scan the real data before committing to an architecture.
On my own time I build AI-workflow infrastructure: a SQLite memory layer with full-text search, an agent-to-agent communication hub, and an observer system that reads an agent’s session logs and proposes edits to its own instructions. I also wrote a 23-article, fact-checked knowledge base on the local-LLM landscape.
Outside of work, I design raid tools for my World of Warcraft guild and keep everything in an Obsidian vault I probably over-š§’d.
Career timeline
20XX ā now Data Platform Engineer (Geospatial pipelines, AWS, Agentic AI systems)
20XX ā 20XX [PRIOR ROLE ā TODO]
Bio
Nate Ramos is a data platform engineer who builds cloud-native geospatial data pipelines and the agentic AI systems that keep them running. His work spans AWS pipeline migrations, MCP server development, agent orchestration, and production data-quality engineering. On his own time he builds AI-workflow infrastructure ā memory layers, multi-agent coordination, self-improving agent systems ā and writes about what actually works when you put AI into production at nateramos.com.