Full-Time

Data Center Development & Infrastructure Finance Lead

Lambda

Lambda

501-1,000 employees

Cloud-based GPU services for AI training

Compensation Overview

$202k - $230k/yr

+ Equity compensation + Commuter stipend

San Francisco, CA, USA + 1 more

More locations: San Jose, CA, USA

Hybrid

Four days per week in the San Francisco or San Jose office; work from home day is Tuesday.

Bachelor's

Category
Finance & Banking (1)
Required Skills
Forecasting
Computer Networking
Investment Banking
Excel/Numbers/Sheets
Financial Modeling

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Requirements
  • A bachelor's degree in Finance, Accounting, Economics, or a related field is required.
  • At least 7 years of experience in FP&A, infrastructure finance, investment banking, or related roles is required, ideally focused on cloud or artificial intelligence infrastructure, data centers, telecommunications, energy, hardware, or industrials.
  • Direct experience with capital expenditure planning and capital allocation, project or development finance, and operating cost modeling is required.
  • Extensive experience in financial modeling and analysis, including constructing complex financial models and interpreting financial statements to support strategic decision-making, is required.
  • Strong Excel skills and experience with financial software systems are required.
  • The ability to manage multiple complex projects in a fast-paced, high-growth environment is required.
  • The ability to work in an ambiguous environment with very little direction is required.
Responsibilities
  • Lead financial modeling for all new data center development projects, including construction, power infrastructure, and network buildout.
  • Own construction budgets, cost-to-complete forecasts, and contingency tracking.
  • Monitor project performance against budget and schedule, identifying risks and mitigation plans.
  • Model project-level returns, including internal rate of return, net present value, and payback, and track performance against underwriting.
  • Develop and maintain the multi-year infrastructure and capacity roadmap.
  • Own capacity models, including supply, demand, and utilization forecasting.
  • Identify capacity risks, including underbuild and overbuild scenarios.
  • Develop commissioning and ramp assumptions for new infrastructure.
  • Own the infrastructure cost model, including power, networking, maintenance, and depreciation inputs.
  • Develop and maintain cost-per-compute and cost-per-workload models.
  • Produce gross margin forecasts and cost sensitivity analyses.
  • Identify opportunities to improve efficiency and reduce cost per unit.
  • Own infrastructure capital expenditure and cost of goods sold budgets.
  • Lead planning cycles for infrastructure and development spend.
  • Deliver regular budget-versus-actual analysis for construction spend, infrastructure costs, capacity utilization, and cost per unit, and present performance insights and recommendations to leadership.
  • Deliver infrastructure and development insights for executive reviews and board materials.
  • Translate complex technical and operational data into clear financial insights.
  • Provide actionable recommendations to drive capital efficiency and margin improvement.
Desired Qualifications
  • Prior experience in a startup or high-growth organization, demonstrating adaptability and flexibility in such environments.

Lambda Labs provides cloud-based GPU services for AI training and inference. Its AI Developer Cloud runs on NVIDIA GH200 Grace Hopper hardware to train large language models and generative AI, offering on-demand and reserved GPUs billed by the hour (for example, $1.99/hour for H100). It differentiates itself through competitive pricing, high availability, and an integrated ML stack with Lambda Stack for easy installation of PyTorch, TensorFlow, CUDA, cuDNN, and NVIDIA drivers, plus Lambda Echelon for owning infrastructure with hosting and support. Its goal is to make scalable AI development and deployment affordable by providing flexible GPU access, reliable hosting, and streamlined software deployment for teams working with large models.

Company Size

501-1,000

Company Stage

Debt Financing

Total Funding

$4.1B

Headquarters

San Jose, California

Founded

2012

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Simplify Jobs

Simplify's Take

What believers are saying

  • On May 7, 2026, Lambda closed a $1 billion J.P. Morgan credit facility.
  • November 2025's $1.5 billion Series E funds chip buys and data-center builds.
  • May 2026 CEO Michel Combes and Chairman John Donovan bring public-company execution experience.

What critics are saying

  • Lambda depends on Nvidia supply; Blackwell or Rubin delays hit 2026 revenue.
  • The 3GW-by-2030 plan requires flawless data-center execution; slippage destroys margins.
  • Microsoft, CoreWeave, and AWS squeeze pricing; one client cancellation exposes concentration.

What makes Lambda unique

  • In May 2026, Lambda launched bare-metal NVIDIA Vera Rubin NVL72 instances.
  • Lambda's March 2026 GB300 photonics stack targets frontier training and inference workloads.
  • On May 20, 2026, Lambda won Hudson River Trading for 1,000 Blackwell systems.

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Benefits

Health Insurance

Dental Insurance

Vision Insurance

401(k) Retirement Plan

401(k) Company Match

Unlimited Paid Time Off

Wellness Program

Commuter Benefits

Growth & Insights and Company News

Headcount

6 month growth

1%

1 year growth

2%

2 year growth

2%
AD HOC NEWS
Aug 11th, 2026
Nvidia arranges $500B AI infrastructure credit, raising Ouroboros risk concerns over chipmaker-lender overlap

Nvidia is arranging over $500 billion in AI infrastructure credit alongside Apollo Global Management, Blackstone, BlackRock, Brookfield Asset Management, Goldman Sachs and KKR, raising concerns about circular financing. The chipmaker may secure up to $125 billion of the total itself. A recent $917 million credit facility with Lambda demonstrates how the system works: customers lacking liquidity can access capital arranged through the consortium to purchase Nvidia hardware. CEO Jensen Huang aims to transform the company's graphics chips into an "investable asset class". Critics warn of an "Ouroboros dilemma" — when manufacturers arrange loans for customers to buy their own products, creating a closed loop vulnerable to collapse if actual AI service demand lags infrastructure buildout. Nvidia shares closed at €188.50 on Monday, down 2.67%. The company reports second-quarter fiscal 2027 earnings on 26 August.

Crypto Briefing
Aug 10th, 2026
Lambda secures $1B credit facility to finance Nvidia chip deployment in AI infrastructure expansion

Lambda, an AI cloud infrastructure company, has closed a $1 billion syndicated senior secured credit facility arranged by J.P. Morgan. This represents a nearly fourfold increase from the $275 million facility Lambda established in August 2025. The capital will fund deployment of next-generation Nvidia AI accelerator servers and data centre expansion. Lambda previously secured a $500 million loan in 2024 collateralised by Nvidia chips. The company raised $480 million in a Series D funding round in February 2025. Lambda has also established a multibillion-dollar commercial partnership with Microsoft focused on building AI infrastructure. Founded in 2012, Lambda now serves tens of thousands of customers with GPU clusters built for AI training and inference workloads.

Newsworthy AI
Aug 4th, 2026
Lambda completes $6.5M secondary share purchase to expand AI cloud infrastructure

Lambda, an AI cloud infrastructure provider, has completed a secondary share purchase of approximately $6.5 million. Aegis Capital Corp. served as the placement agent for the transaction, which involved the sale of existing shares. The transaction provides liquidity for early investors and employees whilst potentially attracting new institutional investors. Founded in 2012 by machine learning engineers, Lambda operates as "The Superintelligence Cloud" and serves tens of thousands of customers, including AI researchers, enterprises, and hyperscalers. Lambda specialises in delivering high-performance supercomputers for AI training and inference. The company's mission is to make compute as accessible as electricity and provide superintelligence capabilities to everyone. The move comes as AI adoption accelerates across industries and demand for computational power continues to surge.

Lambda
May 7th, 2026
Lambda secures $1B credit facility to expand gigawatt-scale AI infrastructure

Lambda, an AI cloud infrastructure provider, has closed a $1 billion senior secured credit facility, nearly quadrupling its original $275 million facility established in August 2025. J.P. Morgan led the oversubscribed arrangement. The multi-tranche facility will fund expansion of Lambda's next-generation NVIDIA AI accelerator servers and data centre capacity. The company operates gigawatt-scale AI factories serving researchers, enterprises and hyperscalers. Founded in 2012, Lambda describes itself as "The Superintelligence Cloud" and serves tens of thousands of customers. CFO Charles Fisher said the financing addresses "unprecedented demand" from AI customers whilst lowering the company's blended cost of capital. Davis Polk & Wardwell represented Lambda, whilst Willkie Farr & Gallagher advised the lenders on the transaction.

Associated Press
May 5th, 2026
Lambda appoints new CEO and chairman to scale AI infrastructure to 3GW by 2030 after $1.5B Series E

Lambda, an AI cloud infrastructure provider, has appointed Michel Combes as CEO and John Donovan as Chairman of the Board, effective May 2026. Co-founder Stephen Balaban will become CTO, whilst co-founder Michael Balaban takes on the Chief Product Officer role. The leadership restructuring follows Lambda's $1.5 billion Series E funding in November 2025. The company has also recently appointed Jerry Hunter as Vice Chairman of Compute Delivery, Charles Fisher as CFO, and David Connolly as CLO. Combes previously served as CEO of Brightspeed, Softbank International, Sprint and Alcatel-Lucent. Donovan held senior positions at AT&T, including CEO of AT&T Communications. The expanded leadership team aims to help Lambda reach 3GW of AI compute under management by 2030, serving frontier labs, enterprises and hyperscalers.