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Gimlet Labs

Serverless AI inference platform with orchestration

Financial Planning and Analysis Manager - Infrastructure & Corporate

Corporate Finance & FP&AConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USANo salary listedIn-person

About the Job

Requirements

  • Approximately 5–7+ years of experience in financial planning and analysis, strategic finance, or investment banking combined with operating finance.
  • Demonstrated ownership of budgets, forecasts, and performance analysis for operating or corporate functions.
  • Experience supporting a business with significant infrastructure, hardware, or other capital investment.
  • Strong modeling skills and an understanding of how capital expenditures, deployment timing, depreciation, and operating costs affect profitability and cash flow.
  • Experience analyzing spending, headcount, cost drivers, and opportunities for operational improvement.
  • Strong data analytics skills and attention to detail.
  • Experience partnering with technical teams and department leaders to develop realistic operating plans.
  • Ability to manage recurring deliverables and independently investigate changes in business performance.

Responsibilities

  • Manage budgets and forecasts for infrastructure and assigned corporate functions, including headcount, operating expenses, and capital investments.
  • Build and maintain models for GPU and other hardware purchases, data center capacity, leases, deployment costs, power, cooling, and ongoing operations.
  • Track infrastructure spending and major commitments against plan, identifying changes in timing, cost, or scope that affect the financial outlook.
  • Analyze compute costs, capacity utilization, and operating efficiency to identify opportunities to improve margins and resource allocation.
  • Partner with Infrastructure and the revenue financial planning and analysis partner to translate demand forecasts into capacity and deployment plans.
  • Evaluate investment and spending options through scenario analysis, clarifying tradeoffs between cost, capacity, and cash timing.
  • Maintain key components of the consolidated expense and cash forecasts, contributing to visibility into burn, liquidity, and runway.
  • Support the annual operating plan and periodic reforecasts by coordinating inputs, reviewing assumptions, and consolidating plans across assigned business areas.
  • Partner with Accounting on monthly reporting, accruals, capital expenditure tracking, and budget-versus-actual analysis.
  • Develop cost and operational reporting, prepare analysis for leadership reviews, and improve recurring planning workflows.

Desired Qualifications

  • Experience at a hyperscaler, neocloud, colocation provider, data center developer, or another infrastructure-intensive operator.
  • Familiarity with GPU fleet economics, power and cooling costs, and compute capacity planning.
  • Experience modeling leases, equipment purchases, or infrastructure deployment commitments.
  • Experience with corporate planning, consolidated expense forecasts, and cash forecasting.
  • Familiarity with debt covenants and incorporating financing obligations into operating plans.
  • Experience implementing planning software, automating reporting, or improving financial planning and analysis processes.
  • Experience supporting a technology company through rapid growth and significant capital investment.

About the Company

Gimlet Labs

Serverless AI inference platform with orchestration

Gimlet Labs builds an inference cloud platform that runs and manages complex AI agent workloads across heterogeneous hardware, including GPUs and other accelerators. Its software splits AI tasks and routes each part to the most suitable hardware to improve speed while keeping cost and power use the same. The Gimlet Cloud offers serverless inference for building and scaling multi-agent systems, with the platform handling scheduling and hardware-aware optimization, and it can be deployed in the cloud or in customers’ data centers. It is developing kforge, a toolkit that uses AI agents to automatically generate optimized PyTorch kernels for CUDA, ROCm, and Metal. The goal is to make AI inference a practical, scalable infrastructure problem by coordinating diverse compute to improve performance and efficiency for enterprise workloads.

Company size
51-200
Company stage
Series B
Total funding
$392M
Headquarters
San Francisco, CA
Founded
2023

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