Compute Trader

present of AI; New York (NY); On-site; USD 120,000 - 180,000; Full time

Job summary

Beam operates a serverless cloud platform for running AI inference, sandboxes, and background workloads on on-demand GPUs.

This role focuses on sourcing GPU capacity from datacenter partners and Beam's hardware, then aligning it with customer requests at competitive prices and favorable terms. The candidate should excel in hard negotiation, detail-checking before quotes, and moving fast without waiting for rigid rules.

Qualifications

• A few years in sales, trading, capacity sourcing, or datacenter work.

Responsibilities

• Find GPU capacity from datacenter partners and Beam's hardware, then match it to customer requests at workable prices and terms.
• Negotiate details before sending a quote, ensuring accuracy and clarity.
• Move quickly without clear internal rules while maintaining high diligence.
• Study GPU pricing trends and supplier contracts to improve offers.

Skills

Negotiation

GPU pricing knowledge

Sales experience

Datacenter market network

Contract reading / supplier contracts

Job description

This role is about finding GPU capacity from datacenter partners and Beam's own hardware, then matching it to customer requests at workable prices and terms. It asks for hard negotiation, careful checking of every detail before a quote goes out, and comfort moving fast without clear rules. A strong candidate has a few years in sales, trading, capacity sourcing, or datacenter work, and ideally already knows people in the compute market.

How it fits the AI era

Demand for GPUs is driven by AI, so this job sits right at the point where AI growth meets real hardware limits. Software can help track prices and suppliers, but the work itself depends on trust, negotiation, and judgment about what a supplier can truly deliver. Those human skills stay central, especially when deals involve deposits, delivery dates, and technical fit.

How it builds AI experience

Someone in this role would learn how AI companies buy and use GPUs, including what separates one GPU offer from another in network setup, location, and term. Working with a platform that runs inference and sandboxes gives a close view of what customers need. To prepare, a candidate can study GPU pricing trends, learn the basics of cluster networking, and practice reading spec sheets and supplier contracts.

Worth showing

• Hard negotiation with suppliers
• GPU pricing knowledge
• Network in compute market
• Building trackers and scorecards

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About Beam

Per the company, Beam operates a serverless cloud platform for running AI inference, sandboxes, and background workloads on on-demand GPUs.