StarsWE Brand LogoStarsWE
FDE Hands-On Training Program · Forward Deployed Engineer

FDE Seed Team Recruitment: Cultivating AI Engineering Delivery Capabilities

Deliver end-to-end solutions grounded in real-world business challenges. FDE bridges the gap between model capabilities and customer operations: upstream, it leverages continuously updated large models and toolchains; downstream, it aligns with specific workflows, data boundaries, and acceptance criteria. Our work isn't about training models—it's about deploying AI into live business environments, ensuring stable operation, measurable outcomes, and sustainable maintenance.

View FDE Training
6Knowledge Domain

Complete Capability Map

35capability group

Cover technology to business

146+ Knowledge Points

Includes tools and compliance checklist

4stages

From foundational training to independent delivery

Hands-on Training Program

Address real business challenges and deliver a complete, end-to-end solution.

The training program is organized through a seed team recruitment model: it goes beyond just attending classes, guiding participants to complete the full lifecycle of real-world projects—from onboarding and design to validation, delivery, and review.

FDE Hands-On Training ProgramProject Delivery × Case Studies × Client Communication

Training Mode

Six weeksSection 16Live Practical Training

Full online hands-on training with a fixed weekly schedule and simultaneous feedback on assignments and projects.

Milestones

  • FDE Portfolio
  • Test Evidence
  • Project Handover and Retrospective

Export training

After training and assessment, candidates are selected based on merit for project assignment or trial employment.

16 Lesson Structure

From On-Site Troubleshooting to Continuous Delivery

Five stages, 16 lessons total. Each stage has clear deliverables, culminating in a professional portfolio ready for external presentation.

  1. 1—2 Section

    FDE Boundary and Project Entry

    Define clear boundaries between FDE and algorithm, implementation, and operations. Master background research, stakeholder mapping, and goal alignment during project kickoff.

  2. 3—6 Section

    Requirement Breakdown and Solution Design

    Break down vague business requirements into verifiable scenarios. Deliver the solution document, milestones, and acceptance criteria to conclude the first client presentation.

  3. 7—9 Section

    RAG Delivery and Result Verification

    Build a Retrieval-Augmented Generation (RAG) system with defined test sets and evaluation metrics to validate performance with data, not intuition.

  4. 10—13 Section

    Agent Collaboration and Continuous Delivery

    Orchestrate multi-step agent workflows with exception handling and human fallback, establishing monitoring, logging, and iteration mechanisms for sustainable system operation.

  5. 14—16 Section

    Asset Accumulation, Trial Teaching, and Review

    Consolidate the project into reusable assets and a portfolio. Complete external demo sessions and project retrospectives to prepare for role matching or trial assignments.

Results:FDE Portfolio · Test Evidence · Project Handoff & Retrospective

After training and assessment, top candidates are matched to projects or begin probation.

Dual Instructors

Engineering practice and delivery business are two main tracks, each with its own lead.

The two speakers cover the technical and delivery aspects of the FDE capability triangle, as well as the business capabilities.

Teacher Zhang San's profile picture

Lead Instructor

San ZhangTeacher

Senior Indie Developer · Engineering in Practice

Resume endorsement

  • Tsinghua University Press Authors
  • Open Source Contributor | Rust IoT Architect
  • Reported by Hangzhou Express and other media outlets

Lead the core engineering track: code and architecture, Rust for IoT scenarios, open-source engineering standards, and translating real-world business problems into actionable technical solutions.

Teacher Jingxing's avatar

Lead Instructor

JingxingTeacher

Multi-Agent · AI SaaS · Smart Hardware

Resume endorsement

  • Former Senior Engineer at Alibaba | AI Transformation Consultant
  • AI Agent Entrepreneur | AI Implementation Consultant
  • Third Prize in the Global AI Agent 2025 Special Competition

Lead delivery and commercial initiatives: Multi-agent orchestration, AI SaaS and smart hardware deployment, client communication, and project acceptance. Empower learners to turn their skills into billable services.

Free Trial

Sign up via WeCom for free

Add our Enterprise WeChat to sign up for a trial class. Experience FDE's working style and course pace first, then decide whether to join the full training program.

  1. 1Add WeChat Work
  2. 2Confirm Session
  3. 3Join for free

Enrollment for this trial class ends on 2026/10/20. · Enrollment date will be announced after admission.

Register · Join for Free

Add on WeCom; a consultant will confirm your session. You'll be notified of the start date upon acceptance.

Job Definition

What does FDE actually do?

Upstream consists of continuously updated models and toolchains; downstream comprises specific business processes, data boundaries, and acceptance criteria. FDE's value lies in connecting both ends and ensuring stable operation.

Difference from Algorithm Engineers

Excludes model training and paper replication; focuses on integration, orchestration, tuning, and engineering deployment to solve business problems using existing capabilities.

Difference from Implementation Consultant

Don't just stay at process mapping and solution reporting; get hands-on to configure, call APIs, build workflows, and handle exceptions and performance issues.

Difference from Traditional Operations

Deliverables are not stable legacy systems, but AI applications with evolving capabilities—requiring simultaneous management of performance, cost, and customer expectations.

Capability Triangle

FDE is not a purely technical role. The balance of three key capabilities determines the types of projects you can take on.

  • Technical Capabilities40%

    Programming, APIs, data, cloud, and deployment — delivering solutions that truly work.

  • Delivery Capability35%

    Requirements analysis, project management, quality standards, and customer success ensure project acceptance.

  • Business Capabilities25%

    Pricing, contracts, finance, and the partner ecosystem turn capabilities into sustainable revenue.

Typical Work Scenarios

  • Clarify requirements on-site with the client, breaking down vague requests into verifiable scenarios and metrics.
  • Build knowledge base Q&A, automated ticket classification, or content production workflows for business units.
  • Integrate multimodal models, optimize prompts, and validate output stability.
  • Implement human fallback and escalation mechanisms to mitigate business risks when model errors occur.
  • Deliver documentation, test cases, and training materials to complete customer acceptance.
  • Monitor call quality and costs to drive service renewals and capability expansion.
Knowledge Graph Overview

One-Page Overview of FDE's Full Capability Map

Six knowledge domains, 36 competency groups, and over 150 knowledge points, categorized by learning attributes: Core Required, Advanced Elective, and Practical Projects.

FDE Knowledge Graph · Overview of Six Knowledge Domains (Click to Expand)Zoom in
Core RequiredAdvanced ElectivesPractical ProjectsMaster core essentials first, then supplement with advanced electives based on your track. Practical projects run throughout the entire journey.
Six Knowledge Areas

Break down the competency groups for each knowledge domain one by one.

Click a knowledge domain tag to view the capability groups, detailed knowledge points, and associated learning attributes within that domain.

01

Technical Foundation

Technical Foundation

The foundation of FDE: Programming, toolchains, networking, AI/ML principles, data engineering, and cloud deployment determine whether you can successfully execute your solution.

Programming Languages

Core Required
  • Python
  • JavaScript / TypeScript
  • SQL
  • Shell

Development Tools

Core Required
  • Git / GitHub
  • VS Code / Cursor
  • Docker
  • Linux

Network Fundamentals

Core Required
  • HTTP / HTTPS
  • RESTful API
  • WebSocket
  • Cross-Origin Resource Sharing

AI / ML Fundamentals

Core Required
  • LLM Principles
  • Prompt Engineering
  • RAG Retrieval-Augmented Generation
  • Agent Framework
  • Embeddings & Vector Database
  • Fine-tuning

Data Engineering

Advanced Electives
  • ETL process
  • Data Cleaning
  • Database (PostgreSQL / MongoDB)
  • Data Visualization

Cloud & Deployment

Advanced Electives
  • AWS / Azure / GCP
  • Vercel / Netlify
  • CI/CD
  • Terraform / Infrastructure as Code
  • Monitoring & Logging
Learning Path

Four phases: from building technical foundations to independently delivering projects

Each phase has clear deliverables to ensure learning goes beyond theory. Learners with prior experience can start at Phase 2.

Phase 14-6 weeks

Technology Foundation

Build a foundation in programming, APIs, and AI/ML to independently develop a functional small-scale AI application.

Key Learning Points

  • Programming Languages & Development Tools
  • Networking and API Fundamentals
  • LLM Principles and Prompt Engineering
  • RAG and Vector Databases

Phase Deliverables

  • An Accessible RAG Q&A Demo
  • Personal Code Repository & Deployment Records
  • Common Tool Combinations
View corresponding course
Phase 26-8 weeks

Delivery in Practice

Master the end-to-end process from requirement clarification to acceptance delivery, and drive customer projects forward using standard documentation.

Key Learning Points

  • Requirements Analysis and PRD Writing
  • Agent and Workflow Orchestration
  • Test Strategy and Acceptance Criteria
  • Delivery Documentation and Customer Training

Phase Deliverables

  • A complete project delivery document package
  • A completed practical project
  • Exception Handling and Operations Plan
View corresponding course
Phase 34-6 weeks

Business & Industries

Understand how services are priced, how contracts are structured, and where industry compliance boundaries lie to clearly articulate ROI to clients.

Key Learning Points

  • Business Model and Pricing Strategy
  • Key Points: MSA, SOW, SLA
  • Industry Compliance and Data Boundaries
  • ROI Calculation and Sales Support

Phase Deliverables

  • A service package ready for external quoting
  • Standard Contract and SOW Templates
  • Case Studies and ROI Calculator for Your Industry
View corresponding course
Phase 4Continuous support

Independently manage projects

Independently deliver AI implementation projects as a solo founder or small team to generate stable service revenue.

Key Learning Points

  • Customer Acquisition and POC Validation
  • Project Parallelism & Time Management
  • Partners & Channel Ecosystem
  • Renewal and Service Expansion

Phase Deliverables

  • First Paid Customer & Post-Mortem Record
  • Reusable solution templates
  • Long-term Operations and Renewal Mechanism
Employment and Entrepreneurship Outcomes

After completing FDE, which four career paths can you pursue?

The same capabilities can be deployed for AI adoption within enterprises or monetized as a service by external entrepreneurs.

AI Implementation Roles in Enterprise

01

Responsible for selecting, deploying, and promoting AI applications within the enterprise; this role is experiencing rapid demand growth in digital teams.

  • AI Application Engineer
  • Digital Project Lead
  • Internal Efficiency Tool Development

Suitable for:Technicians and business professionals seeking to join an enterprise or transition into a new role

AI Delivery Services Outsourcing

02

Offer AI implementation projects as a studio or solo company, billed per project or via monthly subscription.

  • Knowledge Base and Intelligent Customer Service Setup
  • Business Process Automation
  • Multimodal Content Production System

Suitable for:Service-based entrepreneurs, freelancers, and technical service studios

Industry Solution Partnerships

03

Partner with industry software vendors and integrators to embed AI capabilities into existing solutions for joint delivery.

  • ISV Capability Enhancement
  • SI Project Technical Subcontracting
  • Publish Cloud Marketplace Solution

Suitable for:Teams with industry resources or channel relationships

Regional Digital Services

04

Provides AI capability diagnostics, training, and pilot implementation services for industrial clusters, parks, and local governments.

  • Regional Enterprise AI Diagnostic
  • Hierarchical Training and Talent Development
  • Pilot project support

Suitable for:Teams and chain-leading enterprises interested in undertaking regional cooperation projects

Courses & Services

Corresponding training camp and in-house training solutions

Individuals can choose the training camp. Enterprises and industrial clusters can opt for customized in-house training solutions.

Corporate Training and Regional Talent Development

Designed for enterprise teams, industrial parks, and industry clusters, FDE training is structured by role: leadership awareness and decision-making, operational skills for business roles, and engineering capabilities for technical roles. Includes pilot project support and internal trainer development.

  • Job Role Analysis and AI Capability Assessment
  • Customize layered course content and assessment criteria
  • Pilot Project Coaching and Outcome Review
  • Local Internal Trainer Development and Case Library Accumulation
View Internal Training Courses
FAQ

Four of the most frequently asked questions about FDE

Yes, but foundational skills must be established. Phase 1 covers Python, API integration, and basic command-line usage with runnable sample projects. Beginners should allocate 4-6 weeks to build technical foundations before starting delivery projects.

Algorithm engineers focus on model training and performance improvement. FDE professionals concentrate on deploying existing models into customer workflows and ensuring stable operation. FDE roles prioritize engineering, communication, and project management skills over research papers and hyperparameter tuning.

The four phases comprise approximately 14-20 weeks of intensive study, followed by ongoing mentorship. We recommend dedicating 6-8 hours per week to courses, hands-on assignments, and project practice. Learners with prior technical foundations may skip select content in Phase 1.

The platform does not guarantee orders. Phases 3 and 4 will train you to create billable service packages, standard contract templates, and POC validation methods, while the incubation phase connects you with partnership resources. Actual sales depend on your industry network, delivery quality, and market conditions.

View All FAQs

Not sure which path is right for you?

Book a direction diagnosis. We'll assess your technical foundation, industry resources, and available time to determine whether you should start from the ground up or jump straight into delivery practice or business capability development.

View FDE courses first

Turn AI capabilities into deliverable, billable services.

The FDE Training Program is organized around six knowledge domains, supported by a four-phase hands-on project and graduation deliverables to help you transition from learning to managing real projects.

View Course Curriculum

You can also add ours directly.WeChat Work