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Course/AI Forward Deployed Engineer

AI Forward Deployed Engineer

Last updatedJuly 2026

The AI Forward Deployed Engineer (FDE) program focuses on creating engineers who can bridge the gap between customers, AI technology, and product development.

01/

What is an AI Forward Deployed Engineer?

An AI FDE is someone who works directly with enterprise customers to understand their business processes, design AI solutions, and integrate LLMs into workflows. They are part software engineer, part solutions architect, and part consultant—a role popularized by companies like Palantir, OpenAI, Anthropic, Scale AI, and many AI startups.

  • Works directly with enterprise customers.
  • Understands customer business processes.
  • Designs AI solutions to solve business problems.
  • Builds prototypes and proofs of concept.
  • Integrates LLMs and AI agents into customer workflows.
  • Communicates effectively with both technical teams and business stakeholders.
02/

Certification Ladder

See where the AI Forward Deployed Engineer certification fits into our comprehensive AI curriculum path.

1

Certified AI Associate

2

Certified Prompt Engineer

3

Certified AI Developer

4

Certified AI Forward Deployed Engineer

5

Certified Enterprise AI Architect

6

Certified AI Transformation Consultant

03/

Module 1: AI & LLM Fundamentals

  • AI landscape
  • Transformers
  • LLM architectures
  • RAG (Retrieval-Augmented Generation)
  • Embeddings
  • Vector databases
  • Prompt engineering
04/

Module 2: Software Engineering

  • Python
  • FastAPI
  • REST APIs
  • Git & GitHub
  • Docker
  • SQL
  • CI/CD basics
05/

Module 3: AI Engineering

  • OpenAI APIs
  • Anthropic APIs
  • Gemini APIs
  • LangChain
  • LlamaIndex
  • Model Context Protocol (MCP)
  • AI agent frameworks
  • Structured outputs
  • Function/tool calling
06/

Module 4: Cloud & Deployment

  • AWS or Azure
  • Kubernetes basics
  • Serverless
  • Authentication
  • Monitoring
  • Logging
  • Security
07/

Module 5: Enterprise Integration

  • Salesforce
  • Microsoft 365
  • SharePoint
  • Slack
  • Jira
  • SAP basics
  • CRM and ERP integrations
08/

Module 6: Customer Engineering

This is what differentiates FDEs:

  • Discovery workshops
  • Requirements gathering
  • Business process mapping
  • Solution architecture
  • ROI estimation
  • Executive presentations
  • Managing pilot projects
09/

Module 7: AI Product Thinking

  • User-centered design
  • Metrics
  • Prompt evaluation
  • Guardrails
  • AI safety
  • Cost optimization
  • Latency optimization
10/

Hands-on Labs

Students should build:

  • AI customer support assistant
  • Internal knowledge assistant using RAG
  • Contract analysis system
  • Sales copilot
  • AI meeting assistant
  • HR onboarding chatbot
  • Financial document analyzer
  • Multi-agent workflow
  • AI workflow with MCP servers
  • End-to-end enterprise AI application
11/

Capstone Project

Teams work with a simulated enterprise customer to:

  1. Conduct discovery.
  2. Define requirements.
  3. Build a proof of concept in 2–3 weeks.
  4. Present the solution to a review panel.

This mirrors the work of actual FDEs.

12/

Soft Skills (Critical)

An FDE spends significant time with customers, so this includes:

  • Technical storytelling
  • Whiteboarding
  • Solution architecture
  • Consulting skills
  • Stakeholder management
  • Negotiation
  • Agile delivery
  • Technical writing
13/

Ideal Graduate Profile

By the end of the program, learners should be able to:

  • Build production-ready AI applications.
  • Integrate AI into enterprise systems.
  • Design and deploy AI agents and RAG solutions.
  • Lead customer discovery workshops.
  • Translate business needs into technical architectures.
  • Deliver AI proofs of concept quickly.
  • Communicate effectively with both executives and engineering teams.