Forward Deployed AI EngineerEnterprise GenAI, RAG & AI Agents

What is a Generative AI Forward Deployed Engineer?

Lecture

SDE vs AI Engineer vs AI FDE: How the Role Changes

Lecture

The Modern GenAI Stack: Models, Context, Tools, Orchestration, Trust and Operations

Lecture

From LLM Applications to Agentic Workflows and Autonomous Agents

Lecture

How to Use This Program and Build Your Portfolio

Lecture

Development Environment Setup: Python, Git, VS Code, Docker and API Keys

Hands-on

FDE Role and GenAI System Fundamentals

Quiz

Python Refresher: Data Structures, Functions and Modules

Lecture

Object-Oriented Python for Production Applications

Lecture

Exceptions, File I/O and Configuration Management

Lecture

Memory Management and Performance Basics

Lecture

Async Python: Event Loops, Coroutines and Tasks

Lecture

Concurrency vs Parallelism and ThreadPoolExecutor

Lecture

Linux for Engineers: Files, Permissions, Processes and Environment Variables

Lecture

Build an Async Python Data-Processing Service

Hands-on

FastAPI Fundamentals and REST API Design

Lecture

Pydantic Validation and Typed Request/Response Models

Lecture

Dependency Injection, Middleware and CORS

Lecture

CRUD Patterns and API Error Handling

Lecture

GraphQL Fundamentals, Schemas, Queries and Mutations

Lecture

API Versioning and Backward Compatibility

Lecture

Test a FastAPI Service with Pytest, Fixtures and Mocks

Hands-on

AWS Fundamentals: Compute, Storage, Databases and Serverless

Lecture

VPCs, Public/Private Subnets, NAT and Security Groups

Lecture

IAM, Least Privilege and Cloud Cost Controls

Lecture

Dockerfiles, Images, Containers and Volumes

Lecture

Docker Compose and Multi-Container AI Applications

Lecture

Deploying Containers with App Runner and ECS Fargate

Lecture

CI/CD with GitHub Actions and Secrets Management

Lecture

Containerize and Deploy a FastAPI AI Service

Hands-on

Train, Validation and Test Sets; Leakage and Bias-Variance

Lecture

Tensors, Forward Pass, Loss Functions and Backpropagation

Lecture

Activation Functions: ReLU and Beyond

Lecture

Optimization: SGD, Adam and AdamW

Lecture

Regularization, Normalization and Learning-Rate Schedules

Lecture

PyTorch Tensors, Autograd and DataLoaders

Lecture

Mixed Precision, Gradient Accumulation and Experiment Tracking

Lecture

Train and Debug a Small Neural Network in PyTorch

Hands-on

Tokenization, Embeddings and Positional Information

Lecture

Self-Attention Step by Step

Lecture

Multi-Head, Multi-Query and Grouped-Query Attention

Lecture

Decoder-Only, Encoder-Only and Encoder-Decoder Architectures

Lecture

Dense Models vs Mixture-of-Experts Models

Lecture

Pretraining Data, Scaling, Checkpoints and Contamination

Lecture

Instruction Tuning, Chat Templates and Tool-Call Formats

Lecture

Long Context, KV Cache and Context Limitations

Lecture

Build a Mini Decoder-Only Transformer and Profile Attention Memory

Hands-on

Prompt Design: Instructions, Context, Examples and Success Criteria

Lecture

Zero-Shot, Few-Shot and Task Decomposition Patterns

Lecture

Reasoning Models, Verification Criteria and Test-Time Compute

Lecture

Structured Outputs with JSON Schema and Pydantic

Lecture

Validation, Repair, Retries and Idempotent Downstream Handling

Lecture

Context Engineering: Write, Select, Compress and Isolate

Lecture

Prompt Versioning, Caching, Routing and Fallbacks

Lecture

Create a Versioned Prompt Package with a Regression Test Suite

Hands-on

RAG Architecture: Ingestion, Retrieval, Generation and Citations

Lecture

Document Parsing, Metadata, Deduplication and Incremental Updates

Lecture

Fixed, Recursive, Structural and Semantic Chunking

Lecture

Embedding Models and Vector Representations

Lecture

Vector Databases: Indexes, Distance Metrics and Metadata Filtering

Lecture

Sparse Search with BM25 and Dense vs Sparse Retrieval

Lecture

Hybrid Search and Reciprocal Rank Fusion

Lecture

Query Rewriting, Multi-Query Search and Reranking

Lecture

RAG Evaluation: Retrieval, Faithfulness, Correctness and Citation Accuracy

Lecture

Build a Permission-Aware Hybrid RAG Service over Enterprise PDFs

Hands-on

Knowledge Graph Fundamentals: Nodes, Edges, Properties and Ontologies

Lecture

Neo4j and Cypher: Modeling and Querying Enterprise Relationships

Lecture

Graph-Based Retrieval and When GraphRAG Is Worth It

Lecture

Multimodal RAG Architecture for Text, Tables, Images and Charts

Lecture

OCR, Layout-Aware Parsing and OCR-Free Retrieval Concepts

Lecture

Vision-Language Models, CLIP and Visual Embeddings

Lecture

Scanned PDFs, Tables, Charts and Multi-Page Visual Context

Lecture

Build a Visual Document Assistant with Graph and Multimodal Retrieval

Hands-on

Choosing Between Prompting, RAG, Tools and Fine-Tuning

Lecture

Data Quality, Licensing, Deduplication and Train/Eval Separation

Lecture

Supervised Fine-Tuning (SFT) Fundamentals

Lecture

LoRA and QLoRA: How Parameter-Efficient Fine-Tuning Works

Lecture

Adapter Rank, Target Modules, Merging and Serving Trade-Offs

Lecture

Preference Learning: Reward Models, DPO and RLAIF

Lecture

RLHF, GRPO and Verifiable-Reward Training Concepts

Lecture

Synthetic Data, Multi-Turn and Tool-Use Training

Lecture

Fine-Tune a Small Open Model and Compare It with Prompt and RAG Baselines

Hands-on

The Augmented LLM: Model + Retrieval + Tools + Memory

Lecture

Workflow Patterns: Chaining, Routing and Parallelization

Lecture

Orchestrator-Worker and Evaluator-Optimizer Patterns

Lecture

Agent Loops: Observe, Decide, Act, Inspect and Stop

Lecture

ReAct, Plan-and-Execute, Router and Supervisor Patterns

Lecture

Designing Safe, Typed and Idempotent Tools

Lecture

LangGraph: State, Nodes, Edges and Conditional Routing

Lecture

Subgraphs, Parallel Execution and Map-Reduce Patterns

Lecture

When Multi-Agent Architecture Helps - and When It Hurts

Lecture

Build and Compare a Workflow, Single Agent and Multi-Agent System

Hands-on

Model Context Protocol (MCP): Host, Client, Server, Tools and Resources

Lecture

Building and Securing an MCP Server

Lecture

Agent-to-Agent (A2A): Skills, Tasks, Messages and Artifacts

Lecture

MCP vs A2A: Choosing the Right Protocol Boundary

Lecture

Slack, Microsoft Teams and Jira Integrations

Lecture

SOAP APIs, WSDL, XML Envelopes and Legacy Error Handling

Lecture

Oracle and MS SQL Server Integration with Safe Parameterized Queries

Lecture

Text-to-SQL Constraints, Read-Only Roles and Fallbacks

Lecture

Build an MCP Tool Server and an Enterprise Integration Agent

Hands-on

Planning, Decomposition, Task Graphs and Completion Checks

Lecture

Durable Execution: Checkpoints, Resumability and Event-Driven State

Lecture

Retries, Idempotency, Compensating Actions and Cancellation

Lecture

Working State, Thread History, Long-Term Memory and Artifact Stores

Lecture

Context Compaction, Selective Recall and Subagent Isolation

Lecture

Async Background Jobs, Queues, Webhooks and Schedules

Lecture

Code, Shell, Browser and Computer-Use Agents

Lecture

Human-in-the-Loop Approval, Escalation and Safe Resume

Lecture

Build a Long-Running Agent that Survives Interruption and Resume

Hands-on

Authentication vs Authorization: OAuth 2.0, OIDC, SAML and JWT

Lecture

Active Directory, Enterprise SSO and RBAC

Lecture

Data-Level Permissions in RAG and Tool Layers

Lecture

Prompt Injection, Indirect Injection and Jailbreak Threats

Lecture

Excessive Agency, Confused Deputy and Data Exfiltration Risks

Lecture

PII Detection, Masking and Sensitive-Data Redaction

Lecture

NeMo Guardrails and Managed Guardrail Patterns

Lecture

Sandboxing, Egress Control, Secrets and Kill Switches

Lecture

Threat-Model and Secure an Enterprise Agent

Hands-on

Building Golden Datasets, Rubrics and Adversarial Cases

Lecture

Deterministic Graders, LLM Judges and Human Calibration

Lecture

RAG Metrics, Generation Metrics and Business Metrics

Lecture

Agent Trajectory Evaluation: Plans, Tools, Arguments and Policy

Lecture

Production Reliability: Timeouts, Retries, Rate Limits and Circuit Breakers

Lecture

LLM Gateways, Routing, Fallbacks and Centralized API Management

Lecture

Tracing with LangSmith, Langfuse and OpenTelemetry Concepts

Lecture

SLOs, Error Budgets, Cost per Successful Task and Release Gates

Lecture

Build an Agent Evaluation Suite and Production Observability Dashboard

Hands-on

Vision-Language Models for Images, Documents and Video

Lecture

Multimodal Embeddings and Evidence Retrieval

Lecture

ASR, TTS and Speech-to-Speech Systems

Lecture

Realtime Sessions, Streaming and Turn Detection

Lecture

Interruption, Tool Delegation and Voice Safety

Lecture

Embodied and Vision-Language-Action Agent Concepts

Lecture

Build a Voice or Visual Enterprise Assistant

Hands-on

Inference Metrics: TTFT, Inter-Token Latency, Throughput and Goodput

Lecture

KV Cache, Paged Attention and Prefix Caching

Lecture

Continuous Batching, Chunked Prefill and Request Scheduling

Lecture

Quantization, Speculative Decoding and Quality Trade-Offs

Lecture

Tensor, Pipeline, Context and Expert Parallelism

Lecture

Prefill/Decode Disaggregation and KV-Aware Routing

Lecture

Serving with vLLM, SGLang, TensorRT-LLM and NIM

Lecture

NVIDIA NeMo Agent Toolkit, OpenShell, Retriever and Dynamo

Lecture

Benchmark and Optimize an Open-Model Deployment for an Agent Workload

Hands-on

FDE Discovery Workshops: Users, Workflows, Data and Constraints

Lecture

Scoping, Architecture Decisions and Statements of Work

Lecture

Enterprise AI ROI, KPIs, SLAs and Executive Communication

Lecture

UAT, Runbooks, Operations Handoff and User Training

Lecture

Capstone 1: OmniGuard - Secure AI Integration

Capstone

OmniGuard Build: RBAC, Hybrid RAG, Secure SQL and Guardrails

Capstone

Capstone 2: AuditMesh - Multi-Agent Compliance System

Capstone

AuditMesh Build: LangGraph Supervisor, MCP, Human Approval and Cost Tracing

Capstone

Production Review: Quality, Security, Cost and Business KPIs

Lecture

GenAI FDE System Design Interview Patterns

Lecture

RAG, Fine-Tuning, Agent and Security Interview Questions

Lecture

How to Present Your FDE Portfolio and Capstone Architecture

Lecture