AI Engineer
Certification Program

ORCHESTRATE YOUR CAREER TO THE TOP

Become a Leading Engineer at the Forefront of AI

Every tech company is integrating AI into its products, infrastructure, and core workflows. The demand for engineers who can build production-grade AI systems, not just consume APIs, has outpaced the talent pool by a significant margin.

Most developers use LLMs daily. Very few know how to architect an Agentic AI pipeline, orchestrate a multi-agent system, or take an AI application from prototype to production with proper monitoring, failover, and compliance built in. That is why we built this training program.

The GDE AI Engineer program is built for senior developers who recognize that AI is reshaping what companies build, how they build it, and who they hire to do it. This program takes you from writing code that calls AI, to building AI systems that other engineers rely on.

The Skills Companies Are Looking For

From Agentic AI pipelines and multi-agent systems to MCP architecture, vLLM serving, and production observability, every module is built around skills that are in active demand at the companies hiring right now.

Build a Real AI Application

Over the course of the program, you develop a full AI-powered application, from LLM microservice to containerized, monitored production deployment. You leave with a portfolio piece that shows exactly what you can build.

Mentors From the Industry's Front Lines

Your instructors are senior engineers currently building AI systems at companies like Salesforce, Amdocs, Siemens, and Cognyte. They know what engineering teams need, because they’re the ones leading those teams.

Vetted Peers, Built-In Network

Admission is selective by design. Every student is screened for technical background, which means the engineers you learn alongside are the professionals you’ll want to know five years from now.

Learn From Engineers Still Doing the Work

Nikita_Golovko
Nikita Golovko
Principal AI Architect

Director of AI Engineering at Trigo ($238B+) building critical AI platforms and software in the BigTech ecosystem. Former CTO and Head of R&D, engineered large distributed systems and trading platforms. A PhD and featured speaker at the AI Infrastructure Summit, specializes in production-grade architecture.

Daniel_Gotliv
Daniel Gotlieb
Director of AI Engineering

Director of AI Engineering at Trigo ($1B+), leading all AI initiatives and transforming retail technology. Scaled SciPlay from startup through a $2B IPO, managing 11 engineers. Trained hundreds of engineers and architected AI systems for millions of users.

Michael-Winer
Michael Winer
Principal AI Engineer

Principal AI Engineer at Yess (acquired by Amdocs), building and owning production LLM systems, AI recommendation engines, and autonomous analytics platforms end to end. 8+ years delivering ML and AI across ad-tech and SaaS, previously Lead Engineer at AppsFlyer.

Arnon_Goldstein2
Arnon Goldstein
Program Architect Team Lead

Architecture Team Lead at Salesforce, formerly Principal Architect at Microsoft. Led implementation of core platform features supporting Fortune 500 companies. Expert in large-scale enterprise integration and distributed systems with global infrastructure.

Eviatar-Levy-768x768
Eviatar Levi
Founder and AI Architect

Leading AI Architecture at ProciGen.AI, an AI-First company where every Architect orchestrates dozens of agents. Specializes in Production AI, Observability, Evaluation, and Optimization for GenAI and Agentic AI systems. Previously led AI and LLM solutions at HPE and facilitated GenAI workshops.

Yaara_Cohen-768x768
Yaara Cohen
Engineering Manager, Full-Stack & AI

Engineering Manager at Handshaik operating in the business automation space. Has 15 years of experience in software development and R&D leadership, leading AI projects from concept to delivery. Specializes in LLM and agent-based systems, and teaches cohorts and lectures in the field. Previously held Senior and Tech Lead roles at Wix, BigPanda, and other companies.

Lee_Blum
Lee Blum
Lead Software Architect

Designing next-gen security platforms protecting 1,000+ organizations globally. 20+ years architecting petabyte-scale systems for Goldman Sachs, Morgan Stanley, and government agencies. Speaker at O'Reilly Strata, champions practical AI integration in enterprise architecture.

Nikita_Golovko
Nikita Golovko
Principal AI Architect
Daniel_Gotliv
Daniel Gotlieb
Director of AI Engineering
Michael-Winer
Michael Winer
Principal AI Engineer
Arnon_Goldstein2
Arnon Goldstein
Program Architect Team Lead
Eviatar-Levy-768x768
Eviatar Levi
Founder and AI Architect
Yaara_Cohen-768x768
Yaara Cohen
Engineering Manager, Full-Stack & AI
Lee_Blum
Lee Blum
Lead Software Architect

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From Developer to AI Engineer

Claude Code (Engineering Workflows)

 Code generation, debugging, refactoring, Large codebase context (multi-file navigation), Test generation and code validation, Tool use and system interaction, Prompt-driven development workflows, Iterative development and rapid prototyping, Integration into dev workflows

1
Advanced NLP with RAG

 RAG architecture, Basic RAG pipeline Demo using open-source tools (e.g., FAISS, HuggingFace Transformers), document ingestion, embedding, and retrieval, Practical use cases like document Q&A or knowledge-grounded chatbots

2
LLM Integration

Open WebUI, OpenAI API Integration, Anthropic Claude API, AWS Bedrock (Multi-model abstraction, authentication, cost, latency), Llama.cpp (Local LLM Runtime, Quantization, System Requirements), Qwen3, LangChain and LlamaIndex Overview

3
Advanced Prompt Engineering

Prompt management, Core Principles (Instruction Following, Temperature, Top-p, Role Prompting), Chain of Thought (CoT) and ReAct Patterns, Few-shot vs. Zero-shot Prompting, Prompt Evaluation and Iteration, Hands-on Labs with Prompt Engineering

4
Infrastructure and Deployment

 Containerization with Docker, Serving APIs via FastAPI / Flask, Inference at Scale (batch, streaming, real-time), GPU Resource Management, Monitoring and Logging (Prometheus, OpenTelemetry, W&B)

5
Applied LLM Engineering

Model distillation, MCP Server/Client Architecture, Server: Queuing, scheduling, inference management, Client: Structured requests, retries, output handling, Vibe Coding Examples (LLM-powered workflows)

6
AI Agents

 Adding Files for Context, Chatbot development, Agent Design Principles (Autonomy, Reusability, Modularity), Planning and Decision-Making (Tool use, memory, goals), Implementation Patterns (LangChain Agents, ReAct, Finite State Agents), Use Cases: Data extraction, multi-step task automation, tool orchestration, Runtime Management and Cost Implication

7
Automation and Workflow Orchestration

Building and Triggering Workflows (HTTP, Cron, Webhook), Integrating APIs (OpenAI, Claude, custom Python services), LLM Response Handling within n8n nodes, Deploying n8n Workflows on Docker / Cloud, Using n8n for Data Pipelining, Notification and Auto-retraining Hooks

8
Model Reasoning

 Reasoning vs. Pattern Completion in LLMs, Inductive, Deductive, and Abductive Modes, Multi-hop Reasoning and Intermediate Steps, Tool Use to Extend Reasoning Capabilities (e.g., calculators, retrievers), Evaluation Methods for Reasoning Quality (TruthfulQA, BBH, GSM8K)

9
From Code to Production

 End-to-End LLM Automation Application, Custom MCP Client/Server + n8n Workflow Integration, Real-world Deployment (CI/CD, Versioning, Failover), Ethics, Compliance, and Security Considerations in AI Systems

10

Upcoming training programs

Early
Bird Ends:
July 14th
Daniel_Gotliv
United Kingdom - London
August 11, 2026 to November 17, 2026 (Tuesdays)
18:00 to 21:00 Central European Time

Instructor: Daniel Gotlieb, Director of AI Engineering at Trigo

APPLY NOW
11
AUG
Yaara_Cohen-768x768
United States - New York
September 1, 2026 to December 15, 2026 (Tuesdays)
18:00-21:00 Eastern Standard Time

Instructor: Yaara Cohen, Engineering Manager at Handshaik

APPLY NOW
01
SEP
What are the admission requirements
All applicants need at least two years of professional engineering experience in a tech company, working knowledge of at least one backend language (Python preferred), and familiarity with APIs and version control. Candidates go through a screening and evaluation process before admission is confirmed. Upon acceptance, students receive access to a recorded Python foundations course to close any gaps before the program begins.
Is this a course on using AI tools, or on building AI systems
Building. Every module is focused on how AI systems actually work and how to engineer them for production. That means RAG pipelines, LLM integration, agent architecture, MCP server/client patterns, infrastructure, deployment, monitoring, and compliance. Not prompting tools or wrappers that abstract the engineering away.
How practical is the program?
Entirely practical. Every topic is taught through hands-on exercises and applied directly to a rolling project you build throughout the course. By the time the program ends, you'll have developed and deployed a complete AI-powered application, from LLM microservice through containerized, monitored production deployment, that you can bring into any technical interview or use as a foundation for your next project at work.
How is the program structured?
The program runs for 15 weeks, with weekly 3-hour sessions focused on real engineering challenges. Plan for additional time each week for project work, exercises, and self-directed learning. You'll have lifetime access to course materials and recordings, updated as the field evolves.
Who are the instructors?
Senior engineers currently working in AI and engineering leadership at companies including Salesforce, Microsoft, Siemens, Cognyte, and others. Selected based on hands-on experience building production AI systems and a track record of technical leadership. Many of them also interview and hire engineers at their companies, which means they know exactly what the market is looking for.
What kind of payment plans and options do you provide?
We offer flexible payment plans with up to 4 installments of €735 each. Limited scholarships and promotional discounts may be available for qualifying candidates. Contact our admissions team for more details.

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