Notes from the field.
Hiring rubrics, rate indices, and embedded-engineer economics. We publish what we wish we'd had when we started — calibrated for Series A founders shopping for senior AI talent.
- MAY 6, 20267 MIN
Why I'm Betting on LATAM AI Engineers — A Note from Jess Mah
When I founded inDinero in 2009, I tried hiring engineers from everywhere. Twelve years later, the math finally tilted south. Here's the thesis behind FutureProofing — written by Jess Mah.
By Jess Mah - APR 29, 202611 MIN
FutureProofing AI Talent Index — Q2 2026: US AI Engineer Rates by Stack and Seniority
Quarterly benchmarks for senior AI/ML engineer compensation in the US and LATAM, based on Levels.fyi 2026 data, BLS labor stats, and our internal placement data. The reference for builders sizing AI engineering budgets in Q2 2026.
By Jess Mah
- MAY 6, 20267 MIN
What Jess Mah Looks for in a Senior AI Engineer — The 5-Minute Filter
I've sat in 200+ vetting calls with Jess. Watching her interview senior engineers taught me what most hiring playbooks miss — she has one question that filters senior from junior in under 5 minutes. Here's the question, and why it works.
By Gabe Murillo - MAY 6, 20268 MIN
The Mahway Playbook, Applied to AI Engineering Hiring
Mahway invests in 3 startups a year — and built a $1.5B portfolio doing it. We took the same selectivity lens to engineer vetting at FutureProofing. Here's how the Mahway venture creation model maps to the hiring funnel.
By Andrea Barrica - APR 29, 20269 MIN
The Senior AI Engineer Scorecard: How to Vet for Production-Grade ML/LLM Work in 2026
A practical rubric for evaluating senior AI engineers — what to test in each stage, what to score, and the bar a real production AI engineer should clear. Based on the FutureProofing vetting funnel that accepts 12 of every 2,000 candidates.
By Gabe Murillo
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