Work with Andrew
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Big data & analysis pipelines
Data platforms at billion-point scale: Cameral's analysis over a billion-plus public data points, the Dendrite corpus turning US federal datasets into production services, and FINCA's thousands of hours of multilingual field audio made searchable in seconds. Ingestion, ETL, and the analysis layer on top.
Credentials
- Cameral: analysis over a billion-plus public data points
- Dendrite: 40+ data products exposing 443 MCP tools and 313 REST routes over federal datasets
- FINCA: thousands of hours of field audio across 6 languages, searchable in seconds
Why these lanes belong together
The same pattern keeps returning in my work: someone has a system nobody wants to take seriously, and it turns out to be load-bearing. Vacation-home water heaters; a mold inspector's leave-behind sensors; forty federal datasets; surgical training in hospitals with bad connectivity. Every home in a 320-property rental fleet got a digital twin. The mold sensor went through contract manufacturing. The datasets became APIs that AI agents query directly. The surgical platform's prize was $700,000. It runs in Ethiopia. That is the useful part.
Good fit
- Ambiguous zero-to-one systems where the technical direction and the implementation are the same job.
- Data-heavy AI products that must operate reliably in production, under real compliance constraints.
- Problems that cross boundaries: software to hardware, engineering to institutions, prototype to operations.
- Small teams that need a lead who ships alongside them.
Not a fit
- Pure research roles judged on publications. The AI-mechanism work is applied engineering, not an academic track.
- Roles that are exclusively people management with no hands-on technical scope.
- Teams seeking a narrow specialist in a single framework. The value here concentrates where problems cross domains.
- On-site-only roles outside Austin, TX.
A useful first email says what you're building, where it hurts, and what form of help you think you need. Specifics get the fastest reply. hello@andrewfribush.com. The full record is at the engagement ledger, the short version at the résumé. Machine-readable: /career/brief.json · /availability.json.