AI Forward Deployed Engineer
(AI-FDE)
The ultimate professional curriculum bridging Python engineering, Agentic AI (LangGraph & CrewAI), Model Context Protocol (MCP), and DevOps on AWS/Kubernetes to customer-facing forward deployed engineering.
The 8-Step Forward Deployed AI Lifecycle
Click any step to inspect the exact engineering stack, required modules, and production deliverables built in this program.
Complete 14-Phase Syllabus
From pure Python data structures to enterprise multi-agent swarms with MCP, LangSmith tracing, and AWS Kubernetes clusters.
Python, Async, Git, n8n Automation, APIs & Databases
LangChain, Prompting, LangGraph State, pgvector RAG
CrewAI, Model Context Protocol, Observability & Kubernetes
Client Discovery, System Architecture & 7 Real Projects
7 Real-World Projects + Signature Capstone
Every learner builds and ships complete end-to-end systems with production repositories, Docker images, and live AWS endpoints.
AI Research Assistant
Full-stack RAG research engine with document chunking, semantic retrieval, citations generation, and streaming HTTP endpoints.
AI Business Automation System
Autonomous CRM lead triage, inbound email categorization, human-in-the-loop approval gates, and multi-step reporting workflows.
Multi-Agent Research Swarm
Hierarchical multi-agent crew with researcher, fact-checker, synthesizer, and critic agents orchestrating complex domain reports.
Enterprise Knowledge Agent
Knowledge agent connected to enterprise PDFs, DOCX, and SQL stores with hybrid search, metadata filtering, and real-time observability.
AI Voice Agent
Low-latency bidirectional audio system performing speech-to-text, agent execution with tool calling, and high-fidelity speech synthesis.
MCP-Powered AI Agent
Custom Model Context Protocol servers exposing database, local filesystems, and 3rd party APIs for pluggable agent consumption.
Production AI Microservice with Automated CI/CD
Hardened production deployment of an AI agent backend with multi-stage Docker builds, GitHub Actions test suites, AWS ECS/EC2 orchestration, automated SSL, and health check monitoring.
Enterprise AI Operations Platform
The ultimate end-to-end forward deployed challenge. You are given a realistic enterprise business brief to gather requirements, design solution architecture (HLD & LLD), build RAG with pgvector, orchestrate multi-agent swarms with MCP, connect n8n workflow triggers, build FastAPI microservices, inject LangSmith tracing and guardrails, and execute an automated deployment to AWS before presenting your live demo to an executive panel.
Voice & Conversational AI Engineering
Learn speech processing and build real-time Jarvis-style voice assistants with multimodal low-latency pipelines.
Bonus 1: Whisper STT
- • Speech-to-text foundations
- • Audio chunking & transcription
- • Real-time voice command processing
- • Multilingual transcription pipelines
- • Python STT to Agent bridge
Bonus 2: Murf AI TTS
- • High-clarity Text-to-Speech
- • Emotion & tone voice parameters
- • Voice selection & prompt synthesis
- • Low-latency audio streaming
- • Enterprise agent voice personas
Bonus 3: ElevenLabs Voice
- • Next-gen generative voice models
- • Voice cloning principles & ethics
- • Conversational turn-taking agents
- • WebSockets audio packet streaming
- • Production interactive assistant
What You Can Deliver as a Graduate
Directly aligned with real-world Forward Deployed Engineer roles at top AI labs, enterprise tech firms, and AI transformation consultancies.
Business to AI Translation: Discover client requirements and formulate precise technical architectures (HLD/LLD).
Production Agentic Swarms: Build stateful, cyclic multi-agent graphs with LangGraph, CrewAI, and supervisor patterns.
Model Context Protocol (MCP): Build and deploy custom MCP servers to safely connect agents with databases and internal tools.
Enterprise RAG with pgvector: Construct hybrid search, semantic chunking, and re-ranking knowledge engines with zero hallucinations.
Workflow Automation with n8n: Create resilient business workflows connecting CRM, databases, and LLM nodes with human approvals.
FastAPI Async Microservices: Deploy high-throughput backend services with Pydantic validation, streaming tokens, and security.
AI Observability with LangSmith: Monitor token spend, latency, agent trace logs, and execute automated regression evaluation.
Cloud & DevOps (Docker, AWS, K8s): Build CI/CD automation with GitHub Actions, containerize agents, and run on AWS clusters.
Begin Your AI Forward Deployed Journey
Cohort commences on November 5, 2026. Applications are reviewed on a rolling basis.