Tag: hiring
How to hire an applied AI engineer
A standard software interview will not tell you whether someone can hire as an applied AI engineer. The role-defining trait, making an unreliable model dependable, needs a different loop: a real take-home, a rubric that scores failure-mode thinking, and flags you can read in the room.
The applied AI engineer is a reliability engineer
What is an applied AI engineer? Someone who builds reliable production systems on foundation models they did not train. The role is defined less by a skill list than by one trait: failure-mode thinking. Here is what the job is, how it differs from ML engineering, and what makes a good one.
The forgetting curve is the math behind your make-or-buy decision for knowledge work
Humans forget 58% of new information in 20 minutes, 75% in a day, 90% in a week. Ebbinghaus measured this in 1885 and Murre replicated it cleanly in 2015. The forgetting curve is the cognitive-science substrate that decides which retention-critical knowledge work AI can structurally replace at a mid-size company.
Head of AI: the complete hiring guide for mid-size companies
Most mid-size companies need fractional AI leadership before committing to a full-time Chief AI Officer. IBM research shows 76 percent of organizations now have a CAIO, yet MIT CISR found only 7 percent qualify as future-ready for AI. Prove value with part-time strategic guidance before making this hire.
The new AI-augmented job descriptions
The World Economic Forum estimates 39 percent of core skills will change by 2030. Every role is becoming AI-augmented. Rewrite job descriptions around human-AI collaboration, not just AI tool usage.