What you’ll learn
Few candidates have ‘FDE’ on a resume. This chapter grades adjacent backgrounds (founding engineers, Palantir alumni, Customer Engineers, Solutions Engineers, consultants) for FDE fit.
Early-stage startup engineer is the #1 predictor, you've already done this job.
Look for: talked to first 10 customers personally, built deploy / onboard infrastructure, wore all hats, polyglot full-stack GitHub. The candidate who left a startup that shut down or got acqui-hired is often higher-signal than one riding a head request.
Concept VC counts 335+ Palantir founders, more than half ex-FDEs. Sequoia internally ranks Palantir as the #1 pedigree (Semafor, July 2025). Look for FDSE / FDE / Delta titles, or Deployment Strategist / ‘Echo’ tenure with engineering output.
One of the highest-yield adjacent pools. Google Cloud ‘Customer Engineer’ and Stripe ‘Solutions Architect’ roles are arguably the closest existing analog to AI-lab FDE work.
FDE isn't somebody who brings a playbook.
Quality varies wildly. Specifically: QuantumBlack (McKinsey) and BCG X / BCG Gamma are the ‘special forces of data science’, engineers who code daily in Python, ship Kedro pipelines, productionize models. Look for ‘Senior Data Scientist’, ‘ML Engineer’, or ‘Bespoke Engineering’ titles, 5/4 years tenure (longer = client-management mode).
Hard reject:McKinsey/Bain/BCG generalist with ‘AI/Data Strategy’ only; resume that says ‘synthesized findings’ and ‘drove insights’; Big 4 directors who haven't coded in 3+ years; pure slide-makers.
Key takeaways