GPU & AI Infrastructure – Reserved Deal Desk Broker

Pado

. Build and maintain a live supplier network across neoclouds, aggregators, marketplaces, and colocation-backed operators .

Posted 10/16/2026contractRemote • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in GPU and compute brokering, with a strong focus on negotiating pricing and terms for AI infrastructure. Proficient in managing supplier networks and understanding complex workload requirements across various industries.

Highest-signal resume keywords

Full-Cycle Enterprise SalesGPU Spot And Reserved PricingML Training EnvironmentsExport ControlsSalesforce Proficiency

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

NegotiationCapacity SpecificationsWorkload QualificationRisk AssessmentMarket Intelligence TrackingSLA StructuringTerm Versus Price TradeoffsAccount Intelligence BuildingMulti-GPU ShardingData Residency

Soft Skills

Self-MotivatedProactiveComfortable In High-Growth Environments

Tools & Technologies

SalesforceClayApollo.ioGongModern AI Assistants

Industry Keywords

Neocloud SalesData Center Capacity SalesInfrastructure TradingAI InfrastructureCompute Segregation

Tech Stack

Tools & technologies

Apollo

About the role

Key responsibilities & impact

Build and maintain a live supplier network across neoclouds, aggregators, marketplaces, and colocation-backed operators
Negotiate reserved capacity pricing, prepayment terms, and service levels across H100, H200, B200/B300, GB200/GB300, RTX PRO 6000 Blackwell, and AMD Instinct MI300X/MI355X
Source and qualify AI-native buyers across inference, foundation models, defense technology, robotics and simulation, biotech, and quantitative finance
Translate buyer workloads into capacity specifications suppliers can quote
Match workload requirements against available inventory, including interconnect, bare-metal access, region, term length, memory, and network profile
Run procurement cycles across engineering leaders, CFOs, founders, compliance officers, and board or investment stakeholders
Price to a target spread and own realized gross margin on each originated transaction
Negotiate prepayment and escrow mechanics, payment timing, SLA pass-through, non-circumvention terms, export controls, and cross-border deployment constraints
Work with PADO counsel to mirror upstream and downstream agreements
Assess offtaker creditworthiness, supplier delivery risk, and concentration risk
Maintain Salesforce hygiene and provide accurate executive forecasting
Track spot and reserved pricing by chip, region, and term, feeding market intelligence into the marketplace and product roadmap
Represent PADO at major trade shows and industry events

Requirements

What you’ll need

3+ years of full-cycle enterprise sales in GPU or compute brokering, neocloud sales, data center capacity sales, or infrastructure and commodity trading
Existing relationships on the supply side, demand side, or both
Current knowledge of GPU spot and reserved pricing, chip generations, interconnect, bare-metal versus virtualized infrastructure, region and power cost, term length, and prepayment structure
Ability to qualify workloads without an engineer present
Understanding of ML training environments, foundation model infrastructure, AI infrastructure failure modes, multi-GPU sharding, NVLink, networking, and shared filesystems
Experience structuring one- to five-year commitments carrying 25–50% upfront capital, prepayment and escrow, SLA and service-credit regimes, and term-versus-price tradeoffs
Working knowledge of export controls, cross-border AI deployment, data residency, compute segregation, auditable GPU cost structures, and hardware-level isolation
Rigorous MEDDIC/MEDDPICC or equivalent qualification methodology
Ability to build account intelligence from live business signals, infrastructure decision triggers, and buyer-specific friction points
Proactive use of Salesforce, Clay, Apollo.io, Gong, and modern AI assistants
Self-motivated and comfortable in a high-growth startup environment
Bachelor’s degree in Business, Engineering, or a related technical field, or equivalent market experience
Independent Contractor (1099) engagement

Benefits

Comp & perks

Competitive monthly retainer plus commission credited on realized gross margin and paid as PADO collects
Per-transaction caps apply
Backing and global scale of LG Electronics
Access to a live marketplace with real supplier inventory and demand pipeline
Opportunity to define the reserved deal desk playbook
Collaboration with experts in energy, AI, and data center operations
Remote work arrangement
Approximately 25% travel