GPU & AI Infrastructure – Reserved Deal Desk Broker

This is a fully remote position, open to applicants in United States.

📋 Description

• Establish and sustain a dynamic supplier network encompassing neoclouds, aggregators, marketplaces, and colocation-supported operators.

• Negotiate pricing for reserved capacity, prepayment conditions, and service levels for H100, H200, B200/B300, GB200/GB300, RTX PRO 6000 Blackwell, and AMD Instinct MI300X/MI355X.

• Identify and assess AI-native buyers across sectors such as inference, foundation models, defense technology, robotics and simulation, biotech, and quantitative finance.

• Convert buyer workloads into capacity specifications that suppliers can quote.

• Align workload requirements with available inventory, considering interconnect, bare-metal access, region, term length, memory, and network profile.

• Conduct procurement cycles involving engineering leaders, CFOs, founders, compliance officers, and board or investment stakeholders.

• Price transactions to achieve a target spread and manage the realized gross margin for each transaction initiated.

• Negotiate prepayment and escrow arrangements, payment schedules, SLA pass-through, non-circumvention clauses, export controls, and constraints related to cross-border deployment.

• Collaborate with PADO legal counsel to align upstream and downstream agreements.

• Evaluate offtaker creditworthiness, supplier delivery risk, and concentration risk.

• Ensure Salesforce data integrity and deliver precise executive forecasts.

• Monitor spot and reserved pricing by chip, region, and term, integrating market intelligence into the marketplace and product strategy.

• Represent PADO at significant trade shows and industry gatherings.

⛳️ Requirements

• Minimum of 3 years of comprehensive enterprise sales experience in GPU or compute brokering, neocloud sales, data center capacity sales, or infrastructure and commodity trading.

• Established relationships on either the supply side, demand side, or both.

• Up-to-date knowledge of GPU spot and reserved pricing, chip generations, interconnect, bare-metal versus virtualized infrastructure, regional power costs, term lengths, and prepayment structures.

• Capability to qualify workloads without the presence of an engineer.

• Familiarity with ML training environments, foundation model infrastructure, AI infrastructure failure modes, multi-GPU sharding, NVLink, networking, and shared filesystems.

• Experience in structuring commitments ranging from one to five years, involving 25–50% upfront capital, prepayment and escrow, SLA and service-credit frameworks, and balancing term versus price trade-offs.

• Knowledge of export controls, cross-border AI deployment, data residency requirements, compute segregation, auditable GPU cost structures, and hardware-level isolation.

• Proficient in MEDDIC/MEDDPICC or similar qualification methodologies.

• Ability to generate account intelligence from real-time business signals, infrastructure decision triggers, and specific buyer friction points.

• Proficient use of Salesforce, Clay, Apollo.io, Gong, and contemporary AI assistants.

• Self-driven and comfortable in a fast-paced startup environment.

• Bachelor’s degree in Business, Engineering, or a related technical discipline, or equivalent industry experience.

• Engagement as an Independent Contractor (1099).

🏝️ Benefits

• Competitive monthly retainer along with commission based on realized gross margin, payable upon collection by PADO.

• Caps apply per transaction.

• Support and global reach of LG Electronics.

• Access to a live marketplace featuring real supplier inventory and a demand pipeline.

• Chance to shape the reserved deal desk playbook.

• Collaboration with specialists in energy, AI, and data center operations.

• Flexible remote work arrangement.

• Approximately 25% travel required.