Transition Into High Paying FDE Roles at Top AI Companies

Built for senior engineers who want to become job-ready for Forward Deployed Engineering roles

In-depth, builder-oriented FDE curriculum that bridges deep Agentic AI systems design with executive-level customer delivery
Taught live and mentored by FDEs from top-tier US companies
Includes FDE-specific interview preparation designed to help you crack interviews at frontier labs and top-tier tech companies

4.8

4.7

4.8

Assess Your Fit

Free AI Career Session

Next webinar starts in

00 DAYS

:

00 HR

:

00 MINS

:

00 SEC

Program Overview

Who This Is Built For

Customer Engineers, Solutions Architects, and Solutions Engineers
Software Engineers, DevOps/SRE, and Platform Engineers
Machine Learning Engineers (MLEs), Data Engineers, and Data Scientists
Tech Leads, TPMs, and Engineering Managers who still code

Program Duration

23 weeks across four structured blocks
Progresses from agentic foundations to full FDE delivery
Designed to run alongside a full-time engineering role

Live Learning

Live interactive sessions on concepts and system design
A guided, real-world live project build every week
Dedicated FDE interview-prep modules

Projects

8 live, expert-guided, end-to-end build projects
An enterprise FDE capstone across three cloud stacks
Real customer-shaped systems, not toy problems

Instructors

Current and former AI Engineers and FDEs from tier-1 companies
Practitioners who build and operate agentic systems in production
Guidance grounded in real customer-delivery decisions

What You’ll Build and Learn

Agentic system design, RAG, and multi-agent orchestration
Enterprise wiring: APIs, MCP servers, RBAC, and governance
Evaluation, observability, safety guardrails, and cost control

Multi-Stack Capstone Coverage

Primary: OpenAI Agents SDK + Azure AI Foundry
Alternates: Google ADK + Vertex AI; Claude Agent SDK + Bedrock AgentCore
Graduate ready to ship across Azure, GCP, and AWS

Careers transformed

Average package for alumni

$ 0

Average ROI on course price

0 x

30+ Tools & Tech You’ll Learn

Why Professionals Choose This Program

The FDE skill stack has two sides: AI engineering depth and customer-facing delivery. Most engineers enter with strength on one side.
If you are already customer-facing, such as a Solutions Architect, Customer Engineer, or delivery-side engineer, this program helps you build the AI engineering depth needed for FDE roles.
If you come from a coding or data background, such as MLE, Data Engineer, Data Scientist, or Backend SWE, this program helps you build the customer discovery, scoping, and delivery craft needed to turn your technical depth into FDE work.
Either way, you are not starting over. You build the complete stack needed to move into Forward Deployed Engineering.

The AI-Proof Bet

Deep enough technically to build the systems
Human enough to stay essential as coding is automated
A deliberate hedge against the commoditization of routine code

The Move That Completes Your Stack

Customer-facing engineers add the AI engineering depth
Coding and data engineers add the customer-facing craft
Both walk out with the complete Forward Deployed Engineering skill stack

First-of-Its-Kind, US-Market FDE Program

The first end-to-end FDE program built for the US market
AI engineering, FDE craft, and FDE interview prep in one program
No competitor offers an end-to-end FDE program for US engineers

Production Systems, Not Just Demos

Move past isolated LLM, RAG, and framework demos
Build end-to-end, production-grade agentic systems
Orchestration, safety, evaluation, cost control, and deployment

The Complete FDE Lifecycle

Learn the distinctly FDE craft, not just AI engineering
Customer discovery, problem framing, scoping, and commercials
Enterprise wiring, governance, operations, and customer handover

Strong FDE Interview & Career Support

Six weeks of dedicated, FDE-specific interview prep
Decomposition cases, AI system design, and AI-assisted pair coding
Aligned with how Palantir, OpenAI, Anthropic, and Glean actually hire

Learn Hands-On from FAANG+ Mentors

Taught live by current and former AI Engineers and FDEs
Practitioners from tier-1 tech companies and frontier AI labs
Focus on practical decision-making and real production lessons

Multi-Stack Capstone Coverage

Live classes and capstone on OpenAI Agents SDK + Azure AI Foundry
Alternate-stack delivery on Google ADK + Vertex and Claude + Bedrock
Ship confidently across Azure, GCP, and AWS customer environments

This is a living curriculum, continuously updated to reflect how Forward Deployed Engineering is practiced in 2026 and beyond.

Assess Your Fit

Free AI Career Session

Next webinar starts in

00 DAYS

:

00 HR

:

00 MINS

:

00 SEC

Detailed Curriculum: Forward Deployed Engineering Program

AI Engineering Spine

Week 1: Agentic AI Foundations & Reflex Agents

The agent equation: prompt, tools, memory, and LLM
The ReAct loop and the five core agentic design patterns
Agentic-vs-autonomous decision-making and prompt engineering

Live Project: CRM Lead Qualifier Agent
Outcome: Decide when a task needs an agent — and wire up the first one that works.

Weeks 2–3: RAG-Powered Knowledge Agents

Retrieve → augment → generate pipelines with LangChain LCEL
Multi-turn RAG with history and hallucination prevention
Retrieval and generation metrics: Precision@K, groundedness

Live Project: Grounded IT Support Knowledge Assistant
Outcome: Ship a RAG agent that answers only from its sources and proves it with metrics.

Week 4: Multi-Agent Systems (Planner–Executor–Critic)

Role-based design: orchestrator, planner, synthesizer
Task decomposition, routing, and delegation
LangGraph state, nodes, edges, and checkpointer persistence

Live Project: Multi-Agent Travel Planner
Outcome: Split a task that breaks one agent across a team that doesn’t.

Week 5: Conversational & Multimodal Agents

Cascaded STT→LLM→TTS vs. realtime speech-to-speech trade-offs
Reusable LangGraph subgraphs for coordination
Human-in-the-loop approve, review-and-edit, and interrupt patterns

Live Project: Voice-Enabled E-Commerce Assistant with HITL
Outcome: Put a human in the loop without killing the conversation’s UX.

Week 6: Agent Communication Protocols (MCP, A2A, ACP)

Structured tool access via MCP and FastMCP servers
Reliable messaging with finite state machines and validated transitions
Networked agents over the A2A protocol via Google ADK

Live Project: Real Estate Negotiation Simulator
Outcome: Kill the ten failure modes that come from agents talking in free text.

Week 7: Hybrid Search & Retrieval

Sparse vs. dense vectors; k-NN, ANN, and HNSW
SPLADE for learned lexical matching
Hybrid search with Reciprocal Rank Fusion in Qdrant

Live Project: Hybrid Product Search Agent (SPLADE + BGE + RRF)
Outcome: Beat pure-vector recall by fusing lexical and semantic retrieval.

Week 8: Agent Observability, Evaluation & Safety

LangSmith tracing and eval datasets from curated traces
LLM-as-judge, DeepEval metrics, and Guardrails AI
PII redaction with Presidio; cost control via routing, caching, and batching

Live Project: Production-Ready Fintech Support Agent
Outcome: Cut an agent’s cost-per-query while proving its quality didn’t drop.

Week 9: Fine-Tuning & Domain Adaptation

The prompt-vs-RAG-vs-fine-tune escalation framework
The PEFT landscape: LoRA, QLoRA, prefix tuning, and adapters
4-bit quantization, TRL SFTTrainer, and deployment to the HF Hub

Live Project: Fine-Tuned Healthcare Q&A Agent
Outcome: Know when fine-tuning beats prompting — then train and ship an adapter.

Weeks 10–11: Capstone — Enterprise Multi-Agent System

Own a real enterprise problem from architecture to build
Integrate retrieval, orchestration, evals, safety, and cost monitoring
Defend reliability, latency, and cost the way production systems are reviewed

Live Project: LangGraph, LangChain, Streamlit, AWS
Outcome: Stand up a production-grade agentic system you can defend in review.

AI-Assisted Coding

Week 12: Pair Programming with Claude

Real interview intent and problem-solving mindset in the AI era
The structured 5-phase AI-assisted coding framework
The Claude ecosystem: Skills, Projects, Artifacts, and Claude Code

Live project: Building a personalized DSA coach
Outcome: Pair with AI the way the new pair-coding interview round expects.

FDE Spine

Week 13: Customer Discovery & Scoping (FDE capstone starts)

What the FDE role is and how it differs from SWE, SA, and MLE
The 90-minute discovery script and “show me how you do this today”
Stakeholder mapping, RACI, and decision-log discipline

Live project: FDE capstone scenario kicks off
Outcome: Turn a vague AI ask into scoped options with eval-anchored success criteria.

Week 14: SoW, Pricing & Solution Architecture

The 4-milestone estimation framework with risk buffers
SoW writing with eval-anchored acceptance criteria and IP/data clauses
Pricing models and a defensible stack-choice decision matrix

Live project: Capstone work: SoW + pricing rationale + architecture diagram
Outcome: Price and architect an engagement you can defend to a procurement officer.

Week 15: Building Production Agents (OpenAI SDK + Azure Foundry)

Agents, Handoffs, Guardrails, Sessions, and sandboxed execution
Foundry Agent Service vs. Hosted Agents vs. Container Apps
Production hardening, the four multi-agent failure modes, and RAG at scale

Live project: Capstone work: harden the build to production
Outcome: Run hardened production agents on Azure AI Foundry under real load.

Week 16: APIs, MCP Servers & RBAC

Designing APIs as agent tools (FastAPI, OpenAPI, and idempotency)
Building and hardening MCP servers with per-tenant scoping and audit logs
Auth patterns: OAuth 2.0, Entra service principals, and managed identities

Live project: Multi-Tenant MCP Server with RBAC
Outcome: Wire an agent into customer systems with access control at the tool boundary.

Week 17: Evals, Observability & Handover (capstone completion)

Data governance, residency, tenant isolation, and the autonomy ladder
Compliance literacy: SOC 2, HIPAA + BAA, FedRAMP, ISO 27001, and GDPR
Eval suites as a CI deploy gate, an incident fire-drill, and clean handover

Live project: Capstone wraps across all three stacks by end of Week 17
Outcome: Gate deploys on an eval suite and hand the system off without you in the loop.

FDE Interview Prep

Weeks 18–21: Agentic AI System Design Practice

Research agents: planning, tools, and guardrails under interview conditions
Reliable text-to-SQL agents over large schemas
Multi-agent coordination, shared memory, and self-improving verification loops

Live project: Common themes: reliability, evaluation, and cost
Outcome: Design and defend agentic systems live in the system-design round.

Week 22: Decomposition & Case Study Interviews

The Palantir-origin FDE decomposition / case round
Clarify ambiguity, decompose, propose a 4-week scope, and name the riskiest assumption
A 10+ scenario library, the AI-assisted pair-coding round, and architecture interrogation

Live project: Practice cases across multiple industries
Outcome: Run the FDE case round and hold your architecture under hostile questioning.

Week 23: Behavioral & Procurement–Security Interviews

The STAR+ framework and 16 FDE-specific behavioral prompts
Communicating trade-offs and delivering bad news without losing credibility
A procurement/security simulation and a 15-question security bank

Live project: Program closing: portfolio walk-through and recruiter-outreach plan
Outcome: Tell sharp customer-facing stories and survive a security cross-examination.

Bonus Content (Self-Paced)

Foundations track:

AI-driven development foundations, Python essentials, prompting & tooling, multi-agent systems, LLM frameworks (MCP, A2A, ADK), and Development → Deployment (Docker, FastAPI, Kubernetes basics, scalable RAG).

Career track:

DSA (Sorting, Recursion, Trees, Graphs, DP), Resume & LinkedIn Masterclass, Behavioral Interview Strategies, and Offer Negotiation Workshop.

The curriculum is constantly updated as per industry developments and is subject to change.

Detailed Curriculum: Forward Deployed Engineering Program

AI Engineering Spine

Week 1: Agentic AI Foundations & Reflex Agents

The agent equation: prompt, tools, memory, and LLM
The ReAct loop and the five core agentic design patterns
Agentic-vs-autonomous decision-making and prompt engineering

Live Project: CRM Lead Qualifier Agent
Outcome: Decide when a task needs an agent — and wire up the first one that works.

Weeks 2–3: RAG-Powered Knowledge Agents

Retrieve → augment → generate pipelines with LangChain LCEL
Multi-turn RAG with history and hallucination prevention
Retrieval and generation metrics: Precision@K, groundedness

Live Project: Grounded IT Support Knowledge Assistant
Outcome: Ship a RAG agent that answers only from its sources and proves it with metrics.

Week 4: Multi-Agent Systems (Planner–Executor–Critic)

Role-based design: orchestrator, planner, synthesizer
Task decomposition, routing, and delegation
LangGraph state, nodes, edges, and checkpointer persistence

Live Project: Multi-Agent Travel Planner
Outcome: Split a task that breaks one agent across a team that doesn’t.

Week 5: Conversational & Multimodal Agents

Cascaded STT→LLM→TTS vs. realtime speech-to-speech trade-offs
Reusable LangGraph subgraphs for coordination
Human-in-the-loop approve, review-and-edit, and interrupt patterns

Live Project: Voice-Enabled E-Commerce Assistant with HITL
Outcome: Put a human in the loop without killing the conversation’s UX.

Week 6: Agent Communication Protocols (MCP, A2A, ACP)

Structured tool access via MCP and FastMCP servers
Reliable messaging with finite state machines and validated transitions
Networked agents over the A2A protocol via Google ADK

Live Project: Real Estate Negotiation Simulator
Outcome: Kill the ten failure modes that come from agents talking in free text.

Week 7: Hybrid Search & Retrieval

Sparse vs. dense vectors; k-NN, ANN, and HNSW
SPLADE for learned lexical matching
Hybrid search with Reciprocal Rank Fusion in Qdrant

Live Project: Hybrid Product Search Agent (SPLADE + BGE + RRF)
Outcome: Beat pure-vector recall by fusing lexical and semantic retrieval.

Week 8: Agent Observability, Evaluation & Safety

LangSmith tracing and eval datasets from curated traces
LLM-as-judge, DeepEval metrics, and Guardrails AI
PII redaction with Presidio; cost control via routing, caching, and batching

Live Project: Production-Ready Fintech Support Agent
Outcome: Cut an agent’s cost-per-query while proving its quality didn’t drop.

Week 9: Fine-Tuning & Domain Adaptation

The prompt-vs-RAG-vs-fine-tune escalation framework
The PEFT landscape: LoRA, QLoRA, prefix tuning, and adapters
4-bit quantization, TRL SFTTrainer, and deployment to the HF Hub

Live Project: Fine-Tuned Healthcare Q&A Agent
Outcome: Know when fine-tuning beats prompting — then train and ship an adapter.

Weeks 10–11: Capstone — Enterprise Multi-Agent System

Own a real enterprise problem from architecture to build
Integrate retrieval, orchestration, evals, safety, and cost monitoring
Defend reliability, latency, and cost the way production systems are reviewed

Live Project: LangGraph, LangChain, Streamlit, AWS
Outcome: Stand up a production-grade agentic system you can defend in review.

AI-Assisted Coding

Week 12: Pair Programming with Claude

Real interview intent and problem-solving mindset in the AI era
The structured 5-phase AI-assisted coding framework
The Claude ecosystem: Skills, Projects, Artifacts, and Claude Code

Live project: Building a personalized DSA coach
Outcome: Pair with AI the way the new pair-coding interview round expects.

FDE Spine

Week 13: Customer Discovery & Scoping (FDE capstone starts)

What the FDE role is and how it differs from SWE, SA, and MLE
The 90-minute discovery script and “show me how you do this today”
Stakeholder mapping, RACI, and decision-log discipline

Live project: FDE capstone scenario kicks off
Outcome: Turn a vague AI ask into scoped options with eval-anchored success criteria.

Week 14: SoW, Pricing & Solution Architecture

The 4-milestone estimation framework with risk buffers
SoW writing with eval-anchored acceptance criteria and IP/data clauses
Pricing models and a defensible stack-choice decision matrix

Live project: Capstone work: SoW + pricing rationale + architecture diagram
Outcome: Price and architect an engagement you can defend to a procurement officer.

Week 15: Building Production Agents (OpenAI SDK + Azure Foundry)

Agents, Handoffs, Guardrails, Sessions, and sandboxed execution
Foundry Agent Service vs. Hosted Agents vs. Container Apps
Production hardening, the four multi-agent failure modes, and RAG at scale

Live project: Capstone work: harden the build to production
Outcome: Run hardened production agents on Azure AI Foundry under real load.

Week 16: APIs, MCP Servers & RBAC

Designing APIs as agent tools (FastAPI, OpenAPI, and idempotency)
Building and hardening MCP servers with per-tenant scoping and audit logs
Auth patterns: OAuth 2.0, Entra service principals, and managed identities

Live project: Multi-Tenant MCP Server with RBAC
Outcome: Wire an agent into customer systems with access control at the tool boundary.

Week 17: Evals, Observability & Handover (capstone completion)

Data governance, residency, tenant isolation, and the autonomy ladder
Compliance literacy: SOC 2, HIPAA + BAA, FedRAMP, ISO 27001, and GDPR
Eval suites as a CI deploy gate, an incident fire-drill, and clean handover

Live project: Capstone wraps across all three stacks by end of Week 17
Outcome: Gate deploys on an eval suite and hand the system off without you in the loop.

FDE Interview Prep

Weeks 18–21: Agentic AI System Design Practice

Research agents: planning, tools, and guardrails under interview conditions
Reliable text-to-SQL agents over large schemas
Multi-agent coordination, shared memory, and self-improving verification loops

Live project: Common themes: reliability, evaluation, and cost
Outcome: Design and defend agentic systems live in the system-design round.

Week 22: Decomposition & Case Study Interviews

The Palantir-origin FDE decomposition / case round
Clarify ambiguity, decompose, propose a 4-week scope, and name the riskiest assumption
A 10+ scenario library, the AI-assisted pair-coding round, and architecture interrogation

Live project: Practice cases across multiple industries
Outcome: Run the FDE case round and hold your architecture under hostile questioning.

Week 23: Behavioral & Procurement–Security Interviews

The STAR+ framework and 16 FDE-specific behavioral prompts
Communicating trade-offs and delivering bad news without losing credibility
A procurement/security simulation and a 15-question security bank

Live project: Program closing: portfolio walk-through and recruiter-outreach plan
Outcome: Tell sharp customer-facing stories and survive a security cross-examination.

Bonus Content (Self-Paced)

Foundations track:

Career track:

DSA (Sorting, Recursion, Trees, Graphs, DP), Resume & LinkedIn Masterclass, Behavioral Interview Strategies, and Offer Negotiation Workshop.

The curriculum is constantly updated as per industry developments and is subject to change.

Live Guided Projects

Built with the instructor during live sessions — step-by-step code-along builds.

CRM Lead Qualifier Agent

Your first LLM-powered agent. Learn how an LLM uses function calling as its reasoning engine, how tools (domain lookup, CRM history, lead scoring) shape behavior, and how a think–act–observe loop drives real decisions.

SupportDesk-RAG

A production-ready RAG system for IT support that answers strictly from retrieved ticket data. Covers OpenAI embeddings, chunking, five LlamaIndex indexing approaches, a LangChain LCEL pipeline, anti-hallucination safeguards, two-layer evaluation, and an agentic RAG extension with memory.

Multi-Agent Travel Planner

An Orchestrator → Search → Itinerary Planner → Synthesizer workflow where specialized agents search flights and hotels, generate itineraries, and synthesize recommendations. Built with LangGraph, LangChain, Tavily, SerpAPI.

AxiomCart — Voice-Enabled Shopping Assistant

A stateful, voice-enabled assistant across a LangGraph StateGraph with RAG product discovery, order tracking with HITL interrupts, parallel dispatch, MemorySaver checkpointing, and a Whisper + OpenAI TTS pipeline.

Real Estate Negotiation Simulator

A buyer–seller system where agents communicate via typed Pydantic schemas. Progress from a broken build exposing ten failure modes to a robust architecture with FSM terminal states, MCP-grounded tools, LangGraph routing, and true A2A transport via Google ADK

Hybrid Product Search Agent

Lexical precision plus semantic understanding over Amazon’s ESCI dataset. Generate dual embeddings with SPLADE and BGE-Large, index in Qdrant with HNSW, and merge via Reciprocal Rank Fusion.

Production-Ready Fintech Support Agent

A supervisor + specialist system with full production hardening: LangSmith tracing, DeepEval metrics, Guardrails AI validators, Presidio PII redaction, and tiktoken-powered cost-per-query dashboards.

Domain-Specific Fine-Tuned Agent

A Healthcare Q&A agent: fine-tune a 4-bit quantized Qwen2.5-1.5B-Instruct with QLoRA, deploy the LoRA adapter to the HF Hub, and evaluate side-by-side against the base model in LangSmith.

Projects are subject to change as per industry inputs.

Live Guided Projects

Built with the instructor during live sessions — step-by-step code-along builds.

CRM Lead Qualifier Agent

Your first LLM-powered agent. Learn how an LLM uses function calling as its reasoning engine, how tools (domain lookup, CRM history, lead scoring) shape behavior, and how a think–act–observe loop drives real decisions.

SupportDesk-RAG

A production-ready RAG system for IT support that answers strictly from retrieved ticket data. Covers OpenAI embeddings, chunking, five LlamaIndex indexing approaches, a LangChain LCEL pipeline, anti-hallucination safeguards, two-layer evaluation, and an agentic RAG extension with memory.

Multi-Agent Travel Planner

An Orchestrator → Search → Itinerary Planner → Synthesizer workflow where specialized agents search flights and hotels, generate itineraries, and synthesize recommendations. Built with LangGraph, LangChain, Tavily, SerpAPI.

AxiomCart — Voice-Enabled Shopping Assistant

A stateful, voice-enabled assistant across a LangGraph StateGraph with RAG product discovery, order tracking with HITL interrupts, parallel dispatch, MemorySaver checkpointing, and a Whisper + OpenAI TTS pipeline.

Real Estate Negotiation Simulator

A buyer–seller system where agents communicate via typed Pydantic schemas. Progress from a broken build exposing ten failure modes to a robust architecture with FSM terminal states, MCP-grounded tools, LangGraph routing, and true A2A transport via Google ADK

Hybrid Product Search Agent

Lexical precision plus semantic understanding over Amazon’s ESCI dataset. Generate dual embeddings with SPLADE and BGE-Large, index in Qdrant with HNSW, and merge via Reciprocal Rank Fusion.

Production-Ready Fintech Support Agent

A supervisor + specialist system with full production hardening: LangSmith tracing, DeepEval metrics, Guardrails AI validators, Presidio PII redaction, and tiktoken-powered cost-per-query dashboards.

Domain-Specific Fine-Tuned Agent

A Healthcare Q&A agent: fine-tune a 4-bit quantized Qwen2.5-1.5B-Instruct with QLoRA, deploy the LoRA adapter to the HF Hub, and evaluate side-by-side against the base model in LangSmith.

Projects are subject to change as per industry inputs.

Production-Grade Capstone Projects

Pick from up to 7 production-grade FDE engagements or build your own.

ClaimSense AI

What you’ll build:
A full FDE engagement for a regional auto insurer — a multi-agent + MCP + RAG system that reads claim files (police reports, photos, repair estimates), surfaces high-confidence first decisions to adjusters, and routes edge cases to human review.

Tools & concepts:
OpenAI Agents SDK + Azure AI Foundry, FastMCP, audit logging, multi-agent systems, RAG.

PriorAuth AI

What you’ll build: A full FDE engagement at a hospital network stuck at a 9-day prior-auth turnaround after a HIPAA-blocked pilot. Run discovery, write the SoW, then build a co-pilot that reads the chart note, retrieves payer policy, drafts the auth request with citations, and routes ambiguous cases to a reviewer.

Tools & concepts: OpenAI Agents SDK + Azure AI Foundry, FastMCP, SSO, audit logging, multi-agent systems, RAG (alternate stacks: Google ADK + Vertex; Claude + Bedrock AgentCore).

AI Finance Assistant

What you’ll build:
A six-agent system delivering context-aware investment guidance, portfolio analysis, goal planning, and tax education through a conversational interface.

Tools & concepts:
LangGraph, multi-agent systems, RAG, LLMs, prompt engineering.

AI Content Marketing Assistant

What you’ll build:
A multi-agent platform generating blogs, LinkedIn posts, and visuals with SEO optimization, brand-voice consistency, and platform-specific formatting.

Tools & concepts:
Multi-agent systems, LLMs, SEO basics, multimodal output.

Call Center Intelligence System

What you’ll build:
A seven-stage pipeline that transcribes with speaker diarization, summarizes, and scores each call on a five-dimension QA scorecard, producing compliance flags and downloadable reports.

Tools & concepts:
LangGraph, Whisper, PII redaction, LLMs, report generation.

Multi-Agent Customer Support Assistant

What you’ll build:
A supervisor-coordinated assistant resolving queries against a live relational database, with catalog-search and invoice-lookup agents, identity verification, and anti-hallucination grounding.

Tools & concepts:
Multi-agent systems, LLMs, database integration, memory.

BYOP — Bring Your Own Project

What you’ll build
A personal or professional project of your choice, scoped with mentorship and structured feedback to meet industry standards.

Tools & concepts
Tool and framework selection, best practices, mentorship.

Capstone Projects are subject to change as per industry inputs.

Production-Grade Capstone Projects

Pick from up to 7 production-grade FDE engagements or build your own.

ClaimSense AI

Tools & concepts:
OpenAI Agents SDK + Azure AI Foundry, FastMCP, audit logging, multi-agent systems, RAG.

PriorAuth AI

AI Finance Assistant

AI Content Marketing Assistant

Call Center Intelligence System

Tools & concepts:
LangGraph, Whisper, PII redaction, LLMs, report generation.

Multi-Agent Customer Support Assistant

BYOP — Bring Your Own Project

Capstone Projects are subject to change as per industry inputs.

FAANG+ Instructors to Train You

Get mentored by AI/ML leaders who are driving Agentic AI innovation at top global companies.

Faiza Ghazanfar

Principal AI Product Leader, FDE, Microsoft

Sandhya Kapoor

SVP, Central Platform, AI Infrastructure, Ex-Meta

Nahid Farady

Lead Eng in AI Security, Microsoft

Rishabh Misra

Lead ML Engineer & Researcher, Ex-Google

Ram Vegiraju

ML Architect @ AWS

Samwel Emmanuel

Data & AI Solutions Architect @ Databricks

Assess Your Fit

Free AI Career Session

The IK Experience: What Our Alumni Are Saying

Our engineers land high-paying and rewarding offers from the biggest tech companies, including Facebook, Google, Microsoft, Apple, Amazon, Tesla, and Netflix.

Venkatesh Babu

Senior Director - ISV/SolEx Technical Partner Management

I highly recommend the Applied GenAI course by Interview Kickstart. The PM path was incredibly well-organized, reshaping my thinking on how to leverage Generative AI in product management. The hands-on approach, insightful curriculum, and experienced instructors made it an outstanding learning experience!

Amit Vaswani

Lead Software Engineer, Highnote

I recently completed the Applied Gen AI course at Interview Kickstart, and I couldn't be more impressed. The course was well-structured into modules, making complex concepts easier to digest. For someone without a strong programming background, I appreciated the beginner Python class they offer for non-programmers—it helped build a solid foundation. The instructors are fantastic and always go the extra mile to ensure every question is answered. They are patient and don’t rush through the material, often allowing classes to run over to ensure everyone fully grasps the concepts. One of my favorite features is the 'Expert Connect,' where you can have 1-on-1 sessions with instructors to clear any doubts. Overall, Interview Kickstart provided an exceptional learning experience, and I highly recommend it to anyone looking to uplevel in their career.

Abhishek Singh

Senior Data Analyst, Jeavio

IK is a GOD-Send to me. If you are looking to upskill or transition in your career, IK is the place to be. I joined Data Science Switchup in November-23 and I am loving the 360 degree experience which IK provides. The instructors are professionals who are currently working in the tier-1 companies so the classes have loads of real-life snippets of their experience which adds true value to students like us. The mock sessions and technical sessions helped me immensely to understand the topic at a deeper level. The Ops Team & Success Coaches are superstars who act like a true friend when you need any sort of assistance.

Dwaraknath Bakshi

Senior Director of Engineering, Freshworks

IK has been an integral part of my life for last seven years. Since being part of some of the early batches to most recently pursuing their ML track I have done several courses with them. What amazes me is the approachability of the staff, the proactive support team and professionalism. The material is amazing and profound. Omkar and Niloy to name a few they have amazing faculty who are very knowledgeable and are also great teachers. I can keep raving about IK. It’s definitely a boon to software engineers.

Assess Your Fit

Free AI Career Session

Next webinar starts in

00 DAYS

:

00 HR

:

00 MINS

:

00 SEC

Select a course based on your goals

Agentic AI

Learn to build AI agents to automate your repetitive workflows

Switch to AI/ML

Upskill yourself with AI and Machine learning skills

Interview Prep

Prepare for the toughest interviews with FAANG+ mentorship

FAQs

What is the FDE role, and why now?

A Forward Deployed Engineer sits at the intersection of software engineering, customer-facing implementation, and AI deployment — owning production code inside the customer’s environment. Frontier labs and hyperscalers are investing heavily in the role, US FDE postings have grown sharply, and FDE pay sits meaningfully above Senior SWE.

Who is this program designed for?

Two groups who each bring one half of the FDE skill stack. Customer-facing engineers — Customer Engineers, Solutions Architects, Solutions Engineers — who want AI engineering depth; and coding or data engineers — MLEs, Data Engineers, Data Scientists, backend SWEs, and coding Tech Leads, TPMs, and EMs — who want the customer discovery, scoping, and delivery craft. Both leave with the complete stack.

Do I need prior AI or ML experience?

No. The AI Engineering Spine (Weeks 1–11) builds the foundation — agents, RAG, multi-agent orchestration, evals, fine-tuning — before the FDE-specific block begins. A software-engineering background and Python proficiency are expected.

What makes this different from other AI programs?

It’s the first end-to-end FDE program built for the US market, taught by practitioners with real customer experience, covering the AI Engineering Spine, the FDE Spine, and six weeks of FDE-specific interview prep in one program.

What’s the difference between Live Guided Projects and the Capstone?

Guided projects are built step-by-step with the instructor during live sessions. The capstone is an independent, learner-driven enterprise engagement with instructor support for guidance and unblocking — not step-by-step instruction.

How is the program delivered?

Live interactive sessions on concepts and system design, a guided live project every week, dedicated interview-prep modules, and self-paced foundations and tooling.

How much time will I need each week?

About 4–6 hours per week for live sessions and 6–8 hours for assignments, projects, and self-paced practice.

What tools and technologies will I learn?

Python, LangChain, LangGraph, LlamaIndex, Google ADK; OpenAI, Anthropic, and Gemini APIs; FAISS, Chroma, Qdrant, pgvector; Whisper and OpenAI TTS; LangSmith, DeepEval, Guardrails AI, Presidio; FastMCP and A2A; Hugging Face, PEFT, QLoRA; Streamlit, FastAPI; Docker, AWS, GCP, Azure; the OpenAI Agents SDK and Azure AI Foundry.

What is multi-stack capstone coverage?

The capstone is delivered on a primary stack (OpenAI Agents SDK + Azure AI Foundry) and two alternate stacks (Google ADK + Vertex AI; Claude Agent SDK + Amazon Bedrock AgentCore), so you graduate ready to ship across Azure, GCP, and AWS.

Can I choose my capstone project?

Yes. Choose from pre-defined FDE engagements or use the BYOP option to propose your own, scoped with mentor guidance.

Will I learn when not to use agents?

Yes. A core theme is agentic-vs-deterministic decision-making — when rules, deterministic workflows, or classical ML beat agents, and how to defend that choice in design reviews and interviews.

How production-ready are the systems I’ll build?

They’re designed with production constraints — evaluation, guardrails, cost tracking, observability, deployment, RBAC, and handover. They’re learning systems, but the architecture mirrors real enterprise setups.

Will this help me transition into FDE roles?

Yes. The interview-prep block is structured around the actual loops at companies staffing FDE practices — AI system design, decomposition/case rounds, AI-assisted pair coding, and behavioral and procurement-security rounds.

How are the instructors qualified?

All are current or former AI Engineers / FDEs from tier-1 companies, with hands-on experience building and deploying enterprise agentic systems.

Will there be assignments or exams?

The program is project-based rather than exam-based. Every week pairs a guided live build with independent extension work, tied directly to system design and production trade-offs.

What happens if I miss a live session?

All live sessions are recorded, and instructor support plus discussion channels help unblock you asynchronously.