Nebius AI Cloud — Role-Based Enablement Learning Paths

● Solutions Architect

Technical Mastery Track

Deep technical fluency in Nebius AI Cloud infrastructure, enabling SAs to architect, demo, and defend solutions against complex customer requirements.

12 wks Full ramp

9 modules Total

~52 hrs Seat time

Phase 01 Foundation Weeks 1–2

🏗️

Nebius AI Cloud Architecture Overview

Live Session ⏱ 3 hrs AI Cloud

Learning Objectives

Articulate Nebius's full-stack AI cloud architecture and its differentiation from hyperscalers
Map the Nebius product portfolio (AI Cloud, Token Factory, Managed Services) to customer use cases
Understand data center topology across US, Finland, France, and Iceland regions
Navigate the Nebius console and core IAM concepts

Competency: Platform Awareness

⚡

NVIDIA GPU Portfolio on Nebius — H100 to GB300

Self-Paced Lab ⏱ 4 hrs AI Cloud

Learning Objectives

Compare GPU tiers: HGX H100, H200, B200, GB200 NVL72, and GB300 NVL72 — specs, memory, and use case fit
Explain NVIDIA Blackwell vs Hopper architecture benefits relevant to customer workloads
Match GPU selection to training, fine-tuning, and inference scenarios
Perform hands-on GPU instance provisioning via Nebius console and CLI

Competency: GPU Infrastructure Fluency

🔒

Security, Compliance & Trust Center

Self-Paced ⏱ 2 hrs AI Cloud

Learning Objectives

Navigate Nebius's compliance posture: SOC 2, HIPAA, GDPR, ISO 27001
Explain tenant-level isolation architecture and privacy-by-design principles
Address regulated industry objections (healthcare, finance, EU data residency)
Use the Trust Center to answer security questionnaires in customer engagements

Competency: Security Positioning

✦ Certification Gate — Nebius Foundation Badge

Technical assessment + 30-min architecture walkthrough with SA lead

Phase 02 Practitioner Weeks 3–6

☸️

Managed Kubernetes & Slurm (Soperator) Deep Dive

Workshop + Lab ⏱ 6 hrs AI Cloud

Learning Objectives

Architect multi-node training clusters using Managed Kubernetes with topology-aware scheduling
Configure and operate Soperator for Slurm-based HPC workloads at scale
Implement fault-tolerant job recovery with node health monitoring and auto-repair
Demonstrate hands-on cluster provisioning and workload launch in under 60 minutes

Competency: Orchestration Architecture

🌐

InfiniBand Networking & High-Performance Storage

Technical Lab ⏱ 4 hrs AI Cloud

Learning Objectives

Explain NVIDIA Quantum-X800 InfiniBand fabric and its role in enabling large-scale distributed training
Configure high-performance storage: up to 1 TB/s read throughput for shared filesystems
Compare Nebius storage options: in-house solutions vs WEKA and VAST Data integrations
Design storage architecture for data-parallel and model-parallel training workloads

Competency: Network & Storage Design

🔬

MLOps Stack — MLflow, Spark & Managed Services

Workshop ⏱ 5 hrs AI Cloud

Learning Objectives

Deploy and configure Managed MLflow for experiment tracking and model registry on Nebius
Architect an end-to-end data pipeline using Apache Spark on Nebius Managed Services
Integrate PostgreSQL for model metadata persistence in production ML systems
Demonstrate zero-maintenance managed service deployment to customer stakeholders

Competency: MLOps Architecture

✦ Certification Gate — Nebius Practitioner Badge

Live architecture demo to a mock customer panel + written solution design

Phase 03 Expert Weeks 7–12

🤖

Token Factory API — Production Inference Architecture

Technical Lab ⏱ 5 hrs Token Factory

Learning Objectives

Architect production inference systems using Token Factory's model API with vLLM-optimized throughput
Design latency-optimized serving stacks for reasoning models (DeepSeek R1, multi-modal)
Configure autoscaling inference endpoints for variable production traffic patterns
Position Token Factory vs self-managed inference clusters for different customer personas

Competency: Inference Systems Expert

📊

TCO Modeling & Competitive Displacement

Workshop ⏱ 4 hrs AI Cloud

Learning Objectives

Use the SemiAnalysis TCO framework to model LLM pre-training, RL research, and production inference cost scenarios
Build a side-by-side TCO comparison vs AWS, GCP, Azure, and CoreWeave for target workloads
Articulate Nebius MFU advantages and bare-metal performance differentiation to technical buyers
Develop a value narrative that connects infrastructure efficiency to customer business outcomes

Competency: Competitive & Commercial Expert

🎯

Customer Solution Design — Capstone Lab

Capstone Project ⏱ 8 hrs AI Cloud · Token Factory

Learning Objectives

Respond to a realistic RFP scenario covering model training, fine-tuning, and inference requirements
Produce a complete solution design document including architecture diagram, GPU selection rationale, and TCO model
Deliver a 30-minute solution presentation to a panel of cross-functional reviewers
Receive structured feedback and iterate — simulating the real SA customer engagement cycle

Competency: Certified Nebius SA — Expert

● Account Executive

Sales Fluency Track

Practical technical enablement to help AEs confidently position Nebius AI Cloud, lead discovery conversations, and accelerate deal velocity without becoming engineers.

8 wks Full ramp

9 modules Total

~34 hrs Seat time

Phase 01 Foundation Weeks 1–2

🚀

The Nebius Story — Why AI Cloud, Why Now

Live Session ⏱ 2 hrs AI Cloud

Learning Objectives

Deliver Nebius's core company narrative: NVIDIA Reference Platform Cloud Partner, Nasdaq-listed, $700M investment led by NVIDIA and Accel
Explain the "ultimate cloud for AI innovators" positioning against hyperscalers and GPU-cloud competitors
Identify the three key customer pain points Nebius solves: performance, cost, and time-to-cluster
Pass the 2-minute Nebius elevator pitch assessment with confidence

Competency: Nebius Narrative & Positioning

💡

AI Workload 101 — What Customers Are Actually Building

Self-Paced ⏱ 3 hrs AI Cloud

Learning Objectives

Distinguish between training, fine-tuning, and inference — and why each requires different infrastructure
Recognize AI workload signals in discovery calls (model size, dataset scale, latency requirements)
Map workload types to the correct Nebius solution (AI Cloud clusters vs Token Factory API)
Use real Nebius customer examples (Brave Search, Recraft, Wubble) to anchor conversations

Competency: Technical Discovery Fluency

🏷️

Pricing, Packaging & Commercial Structure

Live Session ⏱ 2 hrs AI Cloud · Token Factory

Learning Objectives

Understand GPU on-demand vs reserved cluster pricing mechanics and when to recommend each
Navigate the Token Factory pricing model and explain per-token economics to customers
Conduct a basic TCO conversation using the SemiAnalysis framework as a credible reference
Identify upsell paths: from on-demand GPU → reserved cluster → dedicated large-scale deployment

Competency: Commercial Confidence

✦ Certification Gate — Nebius Sales Ready Badge

Mock discovery call + pitch assessment with Sales manager

Phase 02 Practitioner Weeks 3–5

⚔️

Competitive Intelligence — Displacing AWS, GCP & CoreWeave

Workshop ⏱ 3 hrs AI Cloud

Learning Objectives

Map Nebius's key differentiators vs hyperscalers: availability speed, MFU performance, bare-metal pricing, AI-native support
Handle "we already use AWS/GCP" objections with a structured displacement conversation
Position Nebius's SemiAnalysis Gold Medal TCO rating as a third-party proof point
Identify competitive vulnerability signals in active deals and adjust the sales motion accordingly

Competency: Competitive Displacement

🏭

Industry Verticals — Life Sciences, Media & Physical AI

Self-Paced ⏱ 3 hrs AI Cloud

Learning Objectives

Apply Nebius's solution portfolio to Life Sciences (drug discovery, genomics), Media & Entertainment (GenAI content), and Physical AI/Robotics use cases
Use Nebius customer success stories (CRISPR-GPT, Simulacra AI, Recraft) as proof-point anchors in vertical conversations
Tailor the Nebius compliance story (HIPAA, GDPR) for regulated industry prospects
Build a vertical-specific discovery question set for each industry

Competency: Vertical Sales Fluency

🤝

Partner Co-Sell Motions with Nebius Partners

Live Session ⏱ 2 hrs Partner Program

Learning Objectives

Understand the three Nebius partner types (VAR, ISV/MSP, Alliance) and how each creates AE deal opportunities
Execute a co-sell motion alongside a Nebius partner — roles, handoffs, and joint account planning
Leverage Nebius partner ecosystem (Trainy, Outerbounds, CentML, Shadeform) for expanded deal coverage
Navigate partner-sourced vs AE-sourced deal compensation structures

Competency: Partner Co-Sell Execution

✦ Certification Gate — Nebius AE Qualified Badge

Full discovery role-play + deal strategy review with Sales Director

Phase 03 Expert Weeks 6–8

📈

Expansion Selling — Land, Adopt & Grow on Nebius

Workshop ⏱ 3 hrs AI Cloud · Token Factory

Learning Objectives

Design a land-and-expand account strategy starting with a single GPU workload through to multi-cluster deployment
Identify expansion triggers: model scale-up, new use cases (RAG, agentic search), partner growth
Build a 6-month account plan with measurable consumption milestones
Use Nebius usage data and observability signals to drive proactive expansion conversations

Competency: Expansion Revenue Strategy

🎓

Executive Selling — Navigating the C-Suite Conversation

Live Workshop ⏱ 3 hrs AI Cloud

Learning Objectives

Translate Nebius's technical differentiation into a CFO-ready business case and CTO-ready architecture story
Handle executive objections around vendor lock-in, long-term Nebius viability, and enterprise SLAs
Leverage Nebius's Nasdaq listing, $700M funding, and NVIDIA partnership as enterprise credibility proof points
Lead a multi-stakeholder executive briefing with confidence and clarity

Competency: Executive Sales Mastery

🏆

AE Capstone — Live Deal Simulation

Capstone ⏱ 4 hrs AI Cloud · Token Factory

Learning Objectives

Navigate a full simulated deal lifecycle: discovery → qualification → technical validation → commercial negotiation → close
Coordinate with a mock SA to deliver a joint customer proposal and technical validation session
Handle a competitive late-stage challenge from a mock AWS team and defend the Nebius selection
Present a closed deal retrospective — what worked, what to replicate, and how to expand the account

Competency: Certified Nebius AE — Expert

● Partner

Partner Competency Track

Build partner independence across the Nebius ecosystem — from initial onboarding through GTM-aligned technical competency and joint go-to-market execution.

10 wks Full ramp

9 modules Total

~38 hrs Seat time

Phase 01 Foundation Weeks 1–3

🌍

Nebius Partner Program — Ecosystem & Opportunity

Live Onboarding ⏱ 3 hrs Partner Program

Learning Objectives

Navigate the three Nebius partner models: VAR (Sales), ISV/MSP (Implementation), and Alliance (Development) — and identify your partnership type's revenue motion
Understand partner benefits: dedicated SA support, co-marketing programs, flexible pricing, and instant compute access
Complete onboarding checklist: portal access, partner tier registration, and first SA introduction
Map your customers' AI workloads to the correct Nebius solution for initial pipeline qualification

Competency: Partner Program Proficiency

🔌

Token Factory API — Quickstart for Partner Builders

Self-Paced Lab ⏱ 4 hrs Token Factory

Learning Objectives

Complete the Token Factory API quickstart: authenticate, invoke a production model endpoint, and parse responses
Integrate Token Factory into a sample partner application using the documented SDK and REST API
Understand token pricing mechanics and how to pass costs through to end customers profitably
Configure rate limits, monitoring, and logging for a production partner deployment

Competency: Token Factory Integration

☁️

Nebius AI Cloud Fundamentals for Partners

Self-Paced ⏱ 3 hrs AI Cloud

Learning Objectives

Understand Nebius AI Cloud core components at a level sufficient to resell and position to end customers
Provision a GPU instance via Terraform — the infrastructure-as-code pattern preferred by partner deployments
Use the Nebius Solution Library on GitHub to accelerate customer deployment with pre-built Terraform recipes
Identify when to escalate to Nebius SA support vs handle independently

Competency: Partner-Level Cloud Fluency

✦ Certification Gate — Nebius Partner Onboarded Badge

Product knowledge assessment + live API integration demo

Phase 02 Practitioner Weeks 4–7

🔧

Building AI Solutions on Nebius — End-to-End Lab

Technical Lab ⏱ 6 hrs AI Cloud · Token Factory

Learning Objectives

Build a complete RAG pipeline on Nebius AI Cloud: data ingestion, embedding, vector storage, and retrieval-augmented generation via Token Factory
Deploy a fine-tuned model using QLoRA on an H100 instance and serve it via a managed inference endpoint
Implement Kubernetes-based autoscaling for a partner SaaS application backed by Nebius GPU compute
Document the architecture and produce a repeatable deployment guide for customer handoff

Competency: Solution Build Competency

🗺️

Partner GTM Alignment — Pipeline & Co-Marketing

Live Workshop ⏱ 3 hrs Partner Program

Learning Objectives

Build a 90-day joint GTM plan with your Nebius Partner Manager including pipeline targets, co-marketing activities, and enablement milestones
Access and activate Nebius co-marketing resources: joint case studies, white papers, and event sponsorship programs
Submit and track deal registrations, and understand the Nebius partner rewards structure
Launch a first joint demand generation campaign using Nebius-approved messaging and creative assets

Competency: GTM Execution Readiness

📋

Partner Support Model & Escalation Playbook

Self-Paced ⏱ 2 hrs AI Cloud

Learning Objectives

Understand Nebius's 24/7 expert support model and how partners access dedicated SA assistance for multi-node customer cases
Use the escalation playbook to triage customer issues: Tier 1 (self-serve docs) → Tier 2 (partner support) → Tier 3 (Nebius SA engagement)
Set customer SLA expectations aligned with Nebius's enterprise support commitments
Navigate the Nebius Status page and incident communication protocols for partner-managed customers

Competency: Partner Support Independence

✦ Certification Gate — Nebius Partner Competent Badge

Joint GTM plan review + solution architecture validation

Phase 03 Expert Weeks 8–10

🏅

Advanced Nebius Solutions — Agentic AI & RAG at Scale

Technical Workshop ⏱ 5 hrs AI Cloud · Token Factory

Learning Objectives

Architect a production-grade agentic search system using Nebius AI Cloud compute and Token Factory inference
Scale a RAG pipeline from prototype to production: chunking strategies, embedding model selection, and retrieval optimization on Nebius
Position Nebius's Agentic Search solution to enterprise customers building internal knowledge systems
Benchmark solution performance and present results as a customer proof of concept

Competency: Advanced Solutions Architect

📰

Joint Case Study Development & Thought Leadership

Collaborative Project ⏱ 3 hrs Partner Program

Learning Objectives

Co-author a joint Nebius + partner customer success story using the Nebius case study framework
Produce a jointly-branded technical white paper or blog post demonstrating partner solution value on Nebius
Submit content for publication on nebius.com and partner channels — following Nebius brand and editorial guidelines
Present the case study at a Nebius partner event or joint webinar

Competency: Partner Thought Leadership

🚩

Partner Capstone — First Joint Customer Win Review

Capstone Review ⏱ 2 hrs AI Cloud · Token Factory

Learning Objectives

Present a closed or advanced-stage partner-sourced deal to the Nebius Partner Manager — detailing discovery, technical validation, and commercial structure
Document a replicable play: how this win pattern can be scaled across the partner's customer base
Receive formal graduation to Nebius Certified Partner status and access advanced co-selling resources
Establish a 6-month pipeline and GTM commitment for the next program phase

Competency: Certified Nebius Partner — Expert