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// METHODOLOGY

How the State of FDE dataset was built

Everything needed to reproduce the 519-posting, 57-employer snapshot. The guiding rule was compliance first: only sources whose own terms permit collection, extracted facts and link-backs rather than republished text, and a deterministic coding rubric anyone can re-run.

1. Sources, and why only these three

Data came from exactly three public, unauthenticated ATS job-board APIs, chosen because each operator's own documentation permits fetching public postings:

  • Lever Postings API - Lever's own docs state published jobs "may be scraped by third parties."
  • Greenhouse Job Board API - "Job Board data is publicly available, so authentication is not required for any GET endpoints."
  • Ashby Public Job Posting API - a documented public, no-auth endpoint for currently published postings.

Deliberately excludedbecause their terms prohibit collection: LinkedIn, Indeed, Wellfound/AngelList, YC Work-at-a-Startup, Google for Jobs, and any re-scraped "open" dataset that launders one of those. Lever's robots signalai-train=no is honored: this data is for statistical/reference analysis, never model training.

2. Collection

A hand-curated seed list of AI-native, data-platform, fintech, dev-tools, and gov-tech companies known to hire FDE-family roles on those three ATSs. Each company's board slug was resolved from its public careers URL, then its one public JSON endpoint was fetched once, rate-limited to no more than one request per second, with an identified User-Agent. No login, no paywall bypass, no IP rotation. The full list of contributing boards ships inside the dataset's meta.boards_contributing.

3. Inclusion and exclusion

Included if the posting was live and its title or description matched the FDE-family lexicon: forward deployed, FDE, FDSE, applied AI/ML engineer, deployment engineer or strategist, field engineer, implementation engineer, and solutions engineer/architect where the role involves production coding or customer-embedded delivery.

Excluded: pure pre-sales or quota-only solutions/sales roles with no coding, support/success roles, internships, expired postings, and duplicate cross-posts (deduped on employer + normalized title + location).

4. The true-FDE authenticity rubric

Each posting is scored 0-2 on five axes. A role counts as a "true FDE" if it scores at least 1 on production coding AND at least 1 on customer embedding AND reports into engineering or product with no quota/OTE language.

Axis012
Production codingno coding / aptitude onlyscripts, some codingships production software
Customer embeddingremote advisory onlysome on-site collaborationembedded / heavy travel
Reporting lineSales / GTMServices / DeliveryEngineering / Product
Comp structurequota + commission + OTEbase + bonusbase + equity, no quota
AI / data depthnoneuses vendor APIsbuilds ML / RAG / pipelines

The coding is a deterministic, temperature-0 keyword rubric, auditable back to text spans in the source posting. It is not human-adjudicated for every row, so spot-checking is recommended.

5. What gets published (and what doesn't)

Published: aggregate statistics, a per-posting fact table of extracted attributes, and a link back to each live posting. Notpublished: verbatim job-description prose (that is the employer's copyright), and anything from a prohibited source. Extracted facts plus a link are citable without republishing anyone's creative text.

6. Limitations

This is the state of FDE hiring among AI-native and infrastructure companies on public ATS boards, not the whole market. It skews to US / venture-backed companies and under-covers large enterprises on private ATSs, EMEA/APAC, and staffing listings. It is a point-in-time snapshot (open roles, not hires), so trend claims need a second edition. Full limitations are listed on the report.