adam_rodriguez
builds the systems that run a business daily
- lead_machineicp → sourced → enriched → drafted · repeatably
- content_enginea brief goes in · finished on-brand content comes out · every day
- data_at_scalehealth-insurance data pipelines — 8M files/day, kafka-driven stages, real-time message-flow observability · MAS
- document_frontendmodular react/typescript viewer — pdf · tiff · text, citation highlighting, lexical + semantic search · ECMS
- ai_integrationmulti-agent pipelines reconciling metadata against document content, at enterprise scale · MAS
- java_migrationwebsphere → spring migration — three applications, one frontend and two backends · PAISdelivered in 3 months against a 1–2 year estimate~$1m in avoided hiring cost (est.) — built in-house instead of bringing on a java contractor
i build systems that keep running after i walk away. that is the whole thing, in both halves of my work.
the day job is enterprise health-insurance data at eight million files a day — kafka-driven pipelines with real-time observability, data-cleanliness and value-validation passes that stop bad values before anything downstream sees them, a react/typescript document viewer handling pdf, tiff and text behind one search surface, and three applications migrated off websphere onto spring in three months. large systems, real constraints, no room to hand-wave.
the other half is smaller and moves faster. a content engine that has run daily in production for five months — a brief goes in, finished on-brand content comes out. a lead machine that sourced 11,795 prospects and separated the warm list from the cold one. same instinct at a different scale: find the process someone repeats by hand, and build the thing that does it every day without being asked.
what i am looking for now is the version of this with more surface area — owning the ai systems a company depends on, not just the service that sits underneath them.