Inclusion Criteria
This site adopts a strict definition of FDE (Forward Deployed Engineer). To qualify, all three of the following must be met:
- On-site or deeply embedded work with customers, rather than purely remote support;
- Hands-on solving of specific customer problems through technical means (writing code, building solutions, constructing systems);
- Accountability for delivery outcomes, rather than a purely pre-sales or purely consulting role.
Region: Main working region is the Chinese market, categorized by city.
Time: Only includes currently active practitioners and their cases that are publicly verifiable from 2026 onward.
Evidence: Only includes individuals who have publicly self-identified through public channels (public GitHub profiles, publicly published content, etc.), with a source link attached to each entry. Anonymous information based solely on speculation is not included.
Content standards: Only neutral, positive, objective facts are included; controversial or negative content is not included.
Scoring and Tiers
Entries are scored by weighted public influence and displayed in three tiers — S / A / B — with no single definitive ranking. Scoring dimensions and weights are public and transparent:
- Open-source community influence (GitHub stars / followers, etc.): 30%
- Short-video content influence (followers, likes/saves, and other public data): 30%
- Depth of work and cases (representative projects, retrospective articles, talks): 25%
- Strength of identity evidence (clarity of public self-identification): 15%
The current version only incorporates the open-source community dimension (preview scores). Full recalculation will occur once the short-video and case dimensions are integrated.
Inclusion Criteria for Each Database
Cases & Resources: "Real-world cases" must be genuine practice records with named clients, projects, or delivery processes (government procurement/award announcements, delivery chronicles, customer cases); "Retrospectives / Methodologies" must focus on FDE and AI implementation with substantive content; "Reports / Interviews" are limited to authoritative media and official channels. All content is archived on-site with the original source noted; high-quality content from self-media tech blogs may be included at discretion.
Company Directory: Admission is based on "providing FDE / AI implementation delivery services to enterprises" — delivery service systems of cloud providers and large model vendors, as well as independent AI implementation service providers, may be included; certification and training institutions are listed as a separate type; general large-model product companies are not included. All official website links have been verified for accessibility; links are not shown where no valid official website could be verified.
Policy Library: Only official policy documents (issued by national ministries or provincial/municipal governments), official authoritative interpretations, and official certification/talent systems are included; media coverage of policies is archived alongside; self-media interpretations and study guides go into Cases & Resources, not the Policy Library.
Data Sources and Updates
Data comes from public channels: public GitHub profiles and repositories, publicly published articles and videos, public job postings, and public reports. The collection pipeline runs on a daily schedule; people are published to the site upon collection (with a quality gate automatically enforcing the inclusion criteria), while other databases go live after verification. Pages display the most recent update time.
Disclaimer and Personal Information Protection
- All information on this site comes from public channels and is provided for industry research and informational reference only; it does not constitute any evaluation of or commitment to any individual or organization.
- This site does not display personal contact information (email, phone, social media DMs, etc.) on any page.
- If any entry contains errors, or if you wish to be included / corrected / removed, please submit via the inclusion and correction channel; requests will be processed within 24 hours after verification.
- This site does not include sensitive personal information such as ID numbers, home addresses, or phone numbers.
FAQ
What is an FDE (Forward Deployed Engineer)?
An FDE (Forward Deployed Engineer) is an engineer dispatched to customer sites to bring AI technology into real business processes: fluent in both technology and business, they write code to solve problems hands-on and are accountable for delivery outcomes. The role was pioneered by Palantir and exploded in China after 2023 with the wave of large models.
What's the difference between an FDE and a pre-sales engineer or delivery engineer?
Pre-sales engineers typically exit after the contract is signed; delivery engineers implement a pre-defined plan. An FDE spans the entire journey: identifying problems at the customer site worth solving with AI, quickly building verifiable solutions, driving them to production, and iterating continuously — the solution keeps evolving based on on-site feedback.
What is the salary level for FDEs?
Public reports show: domestic FDE job postings grew roughly 10x in one year, with top positions offering monthly salaries of 35–70K and starting at 15 months' pay; overseas annual salaries can reach $193,000. Compensation is significantly higher than traditional engineers with the same years of experience.
How do I get into the China FDE Directory?
If you have verifiable public self-identification as an FDE and delivery practice on public channels (GitHub, Douyin, personal websites, etc.), you can submit via "Self-Nomination"; inclusion is free after review, and each entry includes evidence links.
What are the information sources for the directory? Are they reliable?
All entries come from public channels: public GitHub profiles, public Douyin profiles, and publicly published articles and reports. Each entry includes evidence links and the inclusion date; please cite the source when referencing. Errors can be submitted via the inclusion and correction channel and will be processed within 24 hours.
How do I delete or correct my information?
All information on this site comes from public channels. If you wish to correct or remove your entry, contact us via WeChat on the "Self-Nomination" page; requests will be processed within 24 hours after verification.
About the Founder
I am SHI KE, founder of Dropleap, with a Master's in Software Engineering from the University of Science and Technology of China, and a serial entrepreneur.
My 16-year career spans software engineering, internet products, and entrepreneurial management: I started as an engineer and engineering manager, holding technology and product roles at NCS, Tongcheng-Elong, and Hello Inc., and later served as COO of Linhuiba. In 2026, I founded Dropleap in Suzhou, focusing on AI implementation in manufacturing — leading a small team in on-site delivery, helping factories get their first AI scenario running within 2–4 weeks. My conviction is that the success or failure of AI projects lies in deployment, not the model itself — and that conviction goes by another name: FDE.
I turned this understanding into a book: "FDE: AI's Outcome Isn't Decided by the Model", and I am also the author of "AI Coding: Everyone Is a Programmer" and the "WorkBuddy Trilogy".
The reason for building the "China FDE Directory" is simple: FDE job postings grew 10x in a year, but these people are scattered across every corner of GitHub, Douyin, and Maimai, with no map that shows them all. The directory only includes publicly self-identified, verifiable frontline practitioners, with evidence links on every entry — no single definitive ranking, no selling anxiety.
If you are an FDE, you're welcome to self-nominate; if you're hiring FDEs, want AI to truly run in your business, or are simply a peer, feel free to reach out.