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Compute Project Finance Associate

Also called Data centre / Compute Project Finance Associate · Infrastructure Finance · GPU-Backed Lending Analyst

Structures the debt and equity behind data centre builds, GPU-backed lending and power deals. Compute is the largest cost an AI company carries, so how it is financed shapes how fast the company can grow.

What they do

Builds and runs the financial models behind compute deals. That means construction costs, power contracts, lease terms, GPU depreciation and debt sizing. Works with lenders, lawyers, technical advisers and the company's infrastructure team to turn a term sheet into a closed facility. Tests how a deal behaves if chips lose value faster than expected, a customer leaves or a build runs late. Prepares lender materials, tracks conditions to close, and keeps the model in step with the legal documents. Reports to a finance lead or head of infrastructure.

What a strong hire delivers

A clean, auditable model that lenders and the board both trust. One or more financing workstreams moved from term sheet towards close, with clear sensitivities on chip value, utilisation and power cost. A tidy process for lender questions and documents. A shared view with the infrastructure team of what each deal actually commits the company to.

How you can tell they are good

Ask them to walk through a financing they worked on and explain how it was sized. Listen for specifics: debt service cover, residual value assumptions, counterparty risk, what lenders pushed back on. Ask what they would change when the collateral is GPUs, not a power plant. Good candidates are precise about what they did and what the team did.

Why it is hard to fill

Very few people have financed GPU-backed debt, because the market is young. Most strong candidates have a project finance or infrastructure background and have never seen chips as collateral. Titles vary widely between banks, funds and operators, so searching by title misses people. Labs, neoclouds and funds are all competing for the same small group, and the best are rarely looking.

Where to find them

Start with energy and infrastructure project finance teams in banks, advisory firms and infrastructure funds. Look at structured credit and asset-backed finance groups, and at renewable or data centre developers where the associate has handled construction debt. Some come from corporate finance teams at neoclouds or hosting operators. Technical curiosity about hardware matters more than the exact title.

Indicative pay

Not enough published evidence yet to give a fair range for this role, which is common for work this new. We benchmark it for you as part of a search.

Interview questions for a Compute Project Finance Associate

  1. Walk me through a financing you modelled from first draft to close. What was your part in it?

    A strong answer names the asset, structure, lenders and their own tasks. It covers changes made after lender feedback. Worry if they speak only in team terms, cannot explain the numbers, or never saw the deal reach close.

  2. How would you size debt against a pool of GPUs, and what assumptions worry you most?

    Look for depreciation and residual value, contract length, customer quality, utilisation and refinancing risk. They should say which assumptions are weakest and how to test them. Worry if they apply a power-plant template without adjustment.

4 more questions, with what a strong answer covers, are in the Role Kit.

Job description you can post

We are an AI company that needs a Compute Project Finance Associate to help us finance data centre capacity, GPU purchases and power supply. You will work with our finance and infrastructure leads, outside lenders and advisers to structure deals and take them to close.

What you will do

  • Build and maintain financial models for data centre, GPU-backed and power financings
  • Size debt and test downside cases on chip value, utilisation and power cost
  • Support negotiations with lenders, investors and advisers
  • Prepare lender materials and answer diligence questions
  • Track conditions to close and keep models aligned with legal documents
  • Work with infrastructure and engineering teams to understand build and hardware risk

What you will bring

  • Modelled a project, infrastructure or asset-backed financing that reached close
  • Clear understanding of debt sizing, cover ratios and cash flow waterfalls
  • Experience working with lenders, lawyers or technical advisers
  • Able to explain model assumptions simply and defend them
  • Comfortable with contracts such as leases and power agreements
  • Careful, organised and open about errors

Nice to have

  • Exposure to equipment or structured credit
  • Experience in data centre or energy development
  • Interest in how AI hardware is built and used

Free to use and adapt. If it saves you time, a link back to this page is appreciated.

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How we wrote this

Role definitions are our own editorial work, checked against occupational classifications, standards, research and employer pages. Titles vary by company, and this is a description of the work, not a job advert.

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