Career path · Forward Deployed Engineer

Become a ForwardDeployed Engineerin 4 stages

FDEs are technical special ops — embedded with customers to turn cutting-edge AI into real business impact. This path takes you from 2-hour builds to 10× monetized reality.

Preview curriculum

**Course intro — watch first**What an FDE really does, and how this path works
12 min

stages

sub-sections

shippable projects

lessons

800%+

Spike in FDE job listings, driven by the AI boom

Stages across the full translate → build → validate → adopt arc

Escalating projects: rules → ML → RAG and agents

1:1

Learn-by-doing ratio — you build what you watch

01 · Outcomes

What you’ll be able to do

The role is learned by doing. By the end you’ll have shipped real services and can carry a new, ambiguous problem end to end on your own.

Translate existing business processes into AI data journeys with traceable lineage

Write business-value-first PRDs, design specs, and test specs — not vibe code

Build enterprise-grade AI that survives security, compliance, and data-residency audits

Stand up the stack beyond a database — ontologies, knowledge graphs, and vector stores

Engineer context and memory, and ship onto Kubernetes behind private endpoints

Run continuous, delta-based evaluation against strict success criteria

Build AI-native reliability engineering and observability from the ground up

Lead intentional adoption through change management, workflow re-design, and user training

02 · The plan

Four stages, one path end to end

Stage 1

Business Translation

Map the Journey

Customer-engineering documentation, AI data journeys, and lineage from day one.

Stage 2

Production AI Engineering

Build & Scale

Audits, the ontology / knowledge-graph / vector stack, context, and private-endpoint K8s.

Stage 3

Eval & Reliability

Validate & Monitor

Strict success criteria, continuous delta-based eval, and AI-native observability.

Stage 4

Adoption

Transform Workstyle

Beyond lift-and-shift: change management, workflow re-design, and deep user training.

03 · Curriculum

Four stages, 26 lessons

Success requires the full cycle — failing one stage fails everything. Open a stage to see its sub-sections and lessons. Tick the square to mark a lesson done — progress is saved on this device.

Customer Engineering Documentation

Capture the business you’re about to change — before any code.

Video

Documenting the business you’re about to changeCapture existing processes before a single line is generated.

14 min

Lab

Process capture in practiceTurn a messy scenario into a clean current-state process map.

35 min

AI Data Journeys & Lineage

Translate captured processes into AI data journeys with traceable lineage.

Video

From business process to AI data journeyTranslate a documented process into an AI data journey.

16 min

Lab

Map data lineage from day oneBuild the lineage map that keeps later stages from collapsing.

38 min

PRD, Design & Test Specs

Blueprints that start from business value, not vibe code.

Reading

Blueprints that start from business valueWrite PRD, design, and test specs grounded in the journey.

15 min

Quiz

Stage 1 knowledge checkConfirm the documentation → data journey → spec chain.

5 min

Scalability, Security & Compliance

Enterprise audits and data residency are the real bar.

Video

Enterprise audits are the real barSecurity, compliance, and data residency as first-class.

16 min

Lab

Harden a service for auditAdd the security and compliance baseline to a service.

40 min

The Complex AI Stack

Ontologies, knowledge graphs, and vector stores — far beyond a database.

Video

Ontologies, knowledge graphs & vector storesThe enterprise AI stack beyond a frontend and a database.

18 min

Lab

Stand up the knowledge layerWire a knowledge graph and a vector store together.

45 min

Video

Tour the FDE toolboxWalk the ten-phase stack every FDE reaches for.

12 min

Context Management & Memory

Engineer the context and memory the model reasons over.

Reading

Context and memory engineeringManage the context and memory an agent reasons over.

14 min

Fit-K8s-Anywhere & Private Endpoints

Ship onto Kubernetes behind private endpoints.

Lab

Ship onto Kubernetes and private endpointsDeploy the service on K8s behind private endpoints.

42 min

Quiz

Stage 2 knowledge checkConfirm audits, the stack, context, and K8s.

5 min

Success Criteria Alignment

Define the strict criteria an agentic system is judged against.

Video

Define strict success criteria for agentsAlign an agentic system to criteria you can measure.

15 min

Lab

Write the success-criteria contractTurn criteria into a contract the eval harness enforces.

32 min

Continuous Delta-Based Evaluation

Score every change against the last — continuously.

Video

The delta-based evaluation frameworkContinuous evaluation measured as deltas between versions.

17 min

Lab

Build a delta-eval harnessBuild a harness that scores versions continuously.

44 min

Reliability Engineering & Observability

AI-native observability, built from the ground up.

Reading

AI-native observability from the ground upWhy legacy monitoring can’t see an AI-native system.

14 min

Quiz

Stage 3 knowledge checkConfirm criteria, delta eval, and observability.

5 min

Beyond Lift-and-Shift

Rebuilt legacy workflows fail — redesign AI-native instead.

Video

Why rebuilt legacy workflows fail for AILift-and-shift does not work for AI-native solutions.

14 min

Lab

Redesign a workflow AI-nativeTransform a legacy workflow into an AI-native one.

38 min

Change Management & Workflow Re-design

Intentional change management, not a thrown-over-the-wall rollout.

Video

Intentional change managementLead the organizational change a new workflow demands.

15 min

User Training & Ecosystem Orientation

Deep user training so the transformation actually sticks.

Reading

Deep user training & ecosystem orientationTrain users deeply so the new way of working sticks.

13 min

Quiz

Stage 4 knowledge checkConfirm the adoption and change-management essentials.

5 min

04 · Hands-on projects

Three escalating builds are the spine

Every project is built with a coding agent, wrapped in a FastAPI service, then deployed — each one adding a layer. AI surfaces, scores, drafts and routes; a human always decides.

Project 1 · Rules

Explainable rule-based service

An auditable rule engine that scores a record and returns exactly which rules fired — flags and routes to a human, decides nothing.

Claude Code · SQL · FastAPI · Docker

Project 2 · ML

ML review-priority scorer

A trained model that triages a human queue, logs features and predictions to NoSQL, and ships with drift monitoring and a security baseline.

+ ML stack · MongoDB · monitoring

Project 3 · RAG & Agents

RAG + supervisor-agent assistant

Grounded retrieval and a bounded multi-agent that drafts and escalates, with a React console where a person approves, edits or decides.

+ ChromaDB · LangGraph · React · AKS

05 · The FDE toolbox

The 10-phase stack an FDE ships with

Every phase of a deployment — from the first discovery whiteboard to the executive ROI dashboard — has an essential toolbox. You’ll get hands-on with each one across the path.

Business Understanding

Miro / FigJamChatGPT / Claude

Discovery workshops, business process mapping, requirement elicitation.

Data Understanding

Jupyter NotebookDuckDB / DBeaver

Data profiling, SQL exploration, understanding enterprise data.

AI Engineering

LangGraphLangFlowLlamaIndex

Build agent workflows, rapid prototyping, enterprise RAG.

Context Engineering

Neo4j (GraphRAG)Qdrant / pgvector

Knowledge graphs, ontologies, enterprise context, semantic search.

Agent Evaluation

LangSmithLangFuse

Trace, debug, evaluate, benchmark and optimize AI agents.

Enterprise Integration

Postman / BrunoMCP

API integration, enterprise systems connectivity, tool integration.

AI-Assisted Development

CursorClaude Code

AI-powered development, debugging, refactoring, code generation.

Deployment

DockerKubernetes

Containerization, scalable deployment, cloud-native AI applications.

AI Operations (AI-Ops)

Arize PhoenixLangFuseGrafana

Observability, hallucination detection, quality, latency, cost, production health.

Customer Success & ROI

Power BIROI CalculatorValue Dashboard

Measure KPIs, ROI, adoption, executive reporting, customer success.

06 · Who it’s for

Engineers who want to ship, not just spec

There’s no formal FDE training — the role blends DevOps, MLOps, full-stack, consulting and business strategy, and every deployment is different. This path gives you the reps: real problems, real infra, real customers.

Software engineers moving toward customer-facing AI work
Solutions architects and consultants who want to build and own
Teams being upskilled into embedded, high-ownership delivery

“FDEs are technical founders embedded in other companies.”

You don’t train for it in school — you earn it by solving messy, real-world problems with clarity and speed.

Start stage one now

Four stages, three projects, one capstone. Learn the role the only way it’s really learned — by building.

Rate yourself first

Become a ForwardDeployed Engineerin 4 stages

What you’ll be able to do

Four stages, one path end to end

Business Translation

Production AI Engineering

Eval & Reliability

Adoption

Four stages, 26 lessons

Carry a new problem through all four stages — alone

Three escalating builds are the spine

Explainable rule-based service

ML review-priority scorer

RAG + supervisor-agent assistant

The 10-phase stack an FDE ships with

Business Understanding

Data Understanding

AI Engineering

Context Engineering

Agent Evaluation

Enterprise Integration

AI-Assisted Development

Deployment

AI Operations (AI-Ops)

Customer Success & ROI

Engineers who want to ship, not just spec

Start stage one now