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PADO

AI-powered data center energy optimization platform

GPU & AI Infrastructure Reserved Deal Desk Broker

Account ExecutiveConfirmed live in the last 24 hours
Full-timeRemote in USA

About the Job

Requirements

  • At least 3 years of full-cycle enterprise sales in GPU or compute brokering, neocloud sales, data center capacity sales, infrastructure trading, or commodity trading.
  • Maintain current knowledge of GPU spot and reserved pricing and the factors that affect it, including chip generation, interconnect, bare metal versus virtualized infrastructure, region and power cost, term length, and prepayment structure.
  • Qualify workloads without an engineer present; understand machine learning training environments, foundation model infrastructure, AI infrastructure failure modes, multi-GPU sharding, NVLink, and network and shared-filesystem requirements.
  • Structure long-term reserved compute commitments, including one- to five-year terms with 25–50% upfront capital, prepayment and escrow, service-level agreements and service-credit regimes, and term-versus-price tradeoffs; distinguish gross merchandise value from margin.
  • Have working knowledge of export controls, cross-border AI deployment, data residency, compute segregation for defense programs, auditable GPU cost structures for pre-IPO companies, and hardware-level isolation for proprietary model training in capital markets.
  • Apply rigorous qualification methodology such as MEDDIC or MEDDPICC, or equivalent, and build account intelligence from live business signals, infrastructure decision triggers, and buyer-specific friction points.
  • Use AI and go-to-market tools, including Salesforce, Clay, Apollo.io, Gong, and modern AI assistants, to streamline sourcing, automate counterparty research, and shorten deal cycles.
  • Be self-motivated and comfortable contributing to a high-growth startup and building its playbook.
  • Hold a bachelor's degree in Business, Engineering, or a related technical field, or have equivalent market experience.

Responsibilities

  • Build and maintain a live supplier network across neoclouds, aggregators, marketplaces, and colocation-backed operators; negotiate reserved capacity pricing, prepayment terms, and service levels for H100, H200, B200/B300, GB200/GB300, RTX PRO 6000 Blackwell, and AMD Instinct MI300X/MI355X.
  • Source and qualify AI-native buyers, including inference platforms and foundation model developers, defense technology, robotics and simulation, biotech, and quantitative finance, and translate their workloads into supplier-quotable capacity specifications.
  • Match workload requirements—including interconnect, bare-metal access, region, term length, memory, and network profile—to available inventory and determine whether a cluster fits a workload.
  • Navigate procurement cycles by aligning engineering leaders, CFOs, founders, compliance officers, and board or investment stakeholders.
  • Price transactions to a target spread and own gross margin on originated transactions, measured on realized margin rather than gross contract value.
  • Negotiate prepayment and escrow mechanics, payment timing, service-level agreement pass-through, and non-circumvention terms, including export-control and cross-border deployment constraints; work with counsel to mirror upstream and downstream agreements and manage risk to PADO.
  • Assess offtaker creditworthiness, supplier delivery risk, and concentration risk before committing capacity.
  • Maintain Salesforce deal-registration and pipeline records and provide accurate forecasts to the executive team.
  • Track spot and reserved pricing by chip, region, and term, and feed pricing insights into the marketplace and product roadmap.
  • Represent PADO at major trade shows and industry events.

About the Company

PADO

AI-powered data center energy optimization platform

PADO provides an AI-powered platform that helps data centers manage energy use more efficiently. The system collects high-frequency energy data from multiple sources, unifies it, and uses algorithms to automatically adjust power in real time. This balances costs, grid limits, and reliability to keep data centers running smoothly while using less energy. Instead of selling hardware, PADO offers its platform as a service so data centers can improve energy efficiency and operational performance. What sets PADO apart is its proprietary AI that continuously ingests and analyzes large amounts of energy data to enable precise, real-time control, focusing specifically on the data center market in North America and leveraging LG NOVA’s support. The company’s goal is to help customers lower energy costs, reduce waste, and maintain reliable operations at scale.

Company size
11-50
Company stage
Seed
Total funding
$6M
Headquarters
Malibu, CA
Founded
2025

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