FDE (Forward Deployed Engineer): working with customers or business teams to move AI from demo to launch, adoption, and reliable operation
An AI demo may take days. Real deployment still gets stuck on usable data, permissions, system integration, evaluation, workflow change, and whether people adopt it. FDEs carry that last mile with the customer.
Career switchers, project practitioners, and team leaders arrive with different questions. Choose the path closest to where you are now.
For engineers, data and platform builders, product leaders, solutions teams, consultants, and enterprise IT practitioners mapping their strengths and missing evidence.
View transition path Deliver a projectStart with the workflow, permissions, and success criteria, then use the 10-step loop to decide whether to advance, change, or stop.
Open delivery loop Build a teamStart with accountability and project evidence before discussing role titles, capability, collaboration, and organization design.
View evidence standardThis is not a certification track. It is a learning and practice sequence you can start today and support with real project material.
Read the transition guideKnow what an FDE owns and where the boundary sits.
02Use the 10-step canvas on one bounded real problem.
03Record problem, solution, quality, operations, outcomes, and transfer.
04Bring a concrete question and your existing material into the discussion.
Both templates can be copied or downloaded. They are working frameworks still being calibrated through real projects, not certification or compliance standards.
The homepage does not organize content into empty channels. Begin with transition, adoption, and field discovery, then return to the full whitepaper.
Different backgrounds enter FDE with different strengths. Use one real project to close the gaps in field judgment, production delivery, and project evidence.
Read articleAccuracy is not the only launch barrier. Permissions, workflow change, ownership, and operating cost can keep a strong demo inside the meeting room.
Read articleA discovery framework for identifying the user, workflow, data, success criteria, and production constraints before a project begins.
Read articleThe same title can describe very different work. This list only includes opportunities still verifiable on official company pages, with a short note on the shape of each role.
Owns technical discovery, solution design, build, production deployment, customer adoption, and field feedback.
A new-graduate FDSE path spanning customer work, data, applications, architecture, and operational change.
Works with customers to prototype, evaluate, and deploy production-grade generative AI systems at scale.
A solutions and GTM-oriented role deploying AI workflows and integrations through low-code and no-code platforms.
Read a chapter, try a canvas, or bring a real project problem before joining. Concrete context and existing evidence make the discussion more useful.
View group QR codeBring the industry, your role, current approach, constraints, and what you have tried.
Bring materialCanvas and evidence cardShow where the project stands and what is missing without replacing evidence with a story.
Scan to joinFDE WeChat communityThe current QR code lives on one stable page and will be updated there if it changes.
