---
title: 'Senior FP&A Analyst - Supply Chain Finance at Lambda'
canonical: 'https://feeny.ai/job/senior-fp-a-analyst-supply-chain-finance-lambda-san-francisco-9wxjkneart2f'
type: 'job'
last_seen: '2026-11-08'
---

# Senior FP&A Analyst - Supply Chain Finance at Lambda

- **Company:** Lambda
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-11-04
- **Last confirmed live:** 2026-11-08
- **Apply:** https://jobs.ashbyhq.com/Lambda/e5e78c83-e0c8-465d-8d5b-cc92b7c0ecf8

## Job description

Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers. Our customers range from AI researchers to enterprises and hyperscalers. Lambda's mission is to make compute as ubiquitous as electricity and give everyone the power of superintelligence. One person, one GPU.

If you'd like to build the world's best AI cloud, join us.

*Note: This position requires presence in our San Francisco, San Jose, or Bellevue office location 4 days per week; Lambda’s designated work from home day is currently Tuesday.

## About the Role

As a member of the DC / Infrastructure Finance team, you will report to the Manager of DC / Infrastructure Finance and serve as a finance partner to Supply Chain and Strategic Sourcing. You will connect equipment purchasing plans, supplier commitments, delivery schedules, and deployment needs to capital spending and cash forecasts, helping Lambda secure infrastructure capacity while managing cost and inventory exposure.

## What You'll Do

Equipment Capital Planning

- Build and maintain equipment capital spending forecasts across GPUs, servers, networking, storage, and spares by supplier, platform, and deployment
- Translate procurement quantities, unit costs, delivery schedules, and acceptance milestones into equipment spending and deployment cost forecasts
- Track actual costs and purchase commitments against approved investment budgets; explain changes in price, quantity, configuration, and delivery timing

In-Service Timing and Depreciation

- Own equipment in-service timing, from delivery and acceptance through deployment, and the resulting depreciation forecast by asset class, platform, and site
- Combine equipment in-service schedules with facility in-service dates from DC Finance to produce the consolidated infrastructure depreciation forecast
- Reconcile forecast depreciation to the fixed asset register and explain changes driven by timing, useful life, and cost

Supplier Economics and Sourcing Support

- Analyze supplier quotes, bills of materials, and total landed costs, including freight, storage, duties, warranties, and other applicable charges
- Model the financial impact of supplier alternatives, volume commitments, payment terms, and component cost changes to support sourcing negotiations and recommendations
- Track negotiated savings and cost increases against approved assumptions, distinguishing expected savings from realized financial impact

Purchase Commitments and Cash Forecasting

- Own the team’s commitments data across equipment and construction spend, connecting purchase orders, receipts, invoices, and payments into a single source used by DC Finance and Corporate FP&A
- Maintain financial visibility into open purchase orders, deposits, prepayments, contractual commitments, and remaining equipment spending
- Own supplier payment forecasts using contractual terms, delivery and acceptance dates, and invoice status as inputs to the consolidated cash forecast for Corporate FP&A and Treasury
- Assess the cost and cash implications of order changes, delivery delays, expedited shipments, and cancellation or rescheduling provisions

Inventory and Deployment Alignment

- Partner with Supply Chain to track the financial exposure associated with equipment on order, in transit, in storage, and awaiting deployment
- Evaluate aging inventory, spares levels, excess equipment, and obsolescence risk; quantify the cost of holding inventory and potential mitigation options
- Work with capacity planning, DC Finance, and Business / Commercial Finance to align purchasing assumptions with site readiness and demand forecasts, highlighting mismatches and cash tied up in idle equipment

Planning and Accounting Partnership

- Develop equipment, logistics, and supply-related working capital inputs for the annual operating plan, quarterly forecasts, and long-range infrastructure plan
- Partner with Accounting and Supply Chain to reconcile purchase orders, receipts, invoices, deposits, and accrual inputs; support consistent project and asset cost attribution
- Coordinate equipment cost assumptions with DC Finance and provide financial analysis to Treasury and Capital Markets for equipment funding evaluations

Reporting and Process Improvement

- Prepare supplier, equipment cost, commitment, and inventory reporting for business reviews, executive discussions, and investment recommendations
- Provide equipment cost inputs and analysis for investment committee reviews, and compare realized equipment costs and delivery timing with approved assumptions after deployment
- Build and maintain repeatable models and workflows in Pigment and AI-assisted tools, reducing manual spreadsheet work
- Improve procurement data quality and connect purchasing, inventory, and financial systems to produce repeatable forecasts and clear recommendations

You

- Have a Bachelor’s degree in Finance, Accounting, Economics, Supply Chain, or a related field
- Have 4+ years of experience in FP&A, supply chain finance, procurement finance, hardware finance, or a related analytical role
- Have experience forecasting equipment or inventory spending, analyzing supplier costs, or managing purchase commitment and working capital reporting
- Understand how purchase orders, deposits, receipts, supplier payment terms, and inventory movements affect capital spending, in-service timing, depreciation, and cash forecasts
- Possess strong financial modeling and Excel skills, including the ability to analyze unit costs, supplier alternatives, and purchasing scenarios
- Have working proficiency in SQL and experience working with ERP and procurement data (e.g., NetSuite, Coupa)
- Can reconcile detailed procurement and financial data, investigate variances, and turn findings into practical recommendations
- Communicate clearly and partner effectively with sourcing, purchasing, planning, operations, and accounting teams
- Are comfortable working independently in an ambiguous, fast-paced environment while managing multiple projects and deadlines

## Nice to Have

- Experience in hardware, OEM/ODM, or semiconductor supply chain finance, ideally with GPU, server, or networking equipment
- Familiarity with inventory accounting, fixed asset accounting, and depreciation
- Experience with vendor financing, equipment leases, or other equipment funding structures
- Experience with Pigment or another enterprise planning system, and BI tools such as Tableau
- Familiarity with data center deployment ramps, site readiness, or cloud infrastructure unit economics
- Prior experience in a startup or high-growth organization

Salary Range Information The annual salary range for this position has been set based on market data and other factors. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description.

## About Lambda

- Founded in 2012, with 500+ employees, and growing fast
- Our investors notably include TWG Global, US Innovative Technology Fund (USIT), Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, Gradient Ventures, Mercato Partners, SVB, 1517, and Crescent Cove
- We have research papers accepted at top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG
- Our values are publicly available: https://lambda.ai/careers
- We offer generous cash & equity compensation
- Health, dental, and vision coverage for you and your dependents
- Wellness and commuter stipends for select roles
- 401k Plan with 2% company match (USA employees)
- Flexible paid time off plan that we all actually use

## Equal Opportunity Employer

Lambda is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.

## About Lambda

## Company Overview
- **One-liner**: Lambda builds supercomputers and cloud infrastructure for training and deploying large-scale AI models, from single GPUs to gigawatt-scale AI factories.
- **Entity Type**: Private (funding stage not publicly disclosed; founded by ML engineers)
- **Headquarters**: San Francisco, California, USA
- **Founded**: 2012
- **Founders**: Stephen Balaban and Michael Balaban

## Core Business
- Primary industry: AI infrastructure / cloud computing for machine learning.
- Target customers: Frontier AI labs building large foundation models, hyperscalers scaling global AI infrastructure, and enterprises deploying AI in regulated industries (B2B, Enterprise).
- Mission: “Make compute as ubiquitous as electricity and give everyone in America the power of superintelligence” (also “One person, one GPU”).

## Products & Services
- **The Superintelligence Cloud**: A suite of cloud computing offerings specifically built for AI workloads, including:
  - **GPU Instances**: On-demand NVIDIA HGX B200, H100, and GB300 NVL72 instances for prototyping and testing.
  - **Managed Clusters**: Dedicated, single-tenant clusters (e.g., NVIDIA GB300 NVL72, HGX B200/H100) with full management and co-engineering from Lambda’s team.
  - **1-Click Clusters™**: Rapidly deployable clusters for training and inference.
  - **Superclusters**: Large-scale AI factories integrating high-density power, liquid cooling, and high-bandwidth interconnects.
- **AI Infrastructure Hardware**: Modular AI factory designs and NVIDIA-based systems for on-premise or colocation deployment.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed.
- **Key Metric**: Total funding not publicly available; revenue not disclosed.
- **Notable Customers/Partners**: “World’s most advanced AI organizations” (frontier labs, hyperscalers, regulated enterprises). Leadership includes former executives from cloud and networking companies.
- **Growth Signals**: Active hiring across engineering, storage, security, and procurement roles; building AI factories at gigawatt scale; SOC 2 Type II certified; expanding from San Francisco to San Jose, CA.

## Competitive Advantages
- **AI‑First DNA**: 100% of engineering, operations, and support dedicated to AI – founded by ML engineers in 2012.
- **Single‑Tenant Isolation**: Shared‑nothing architecture for security and performance, with hardware‑level isolation.
- **Full‑Stack Expertise**: Co‑engineering from the same team building the infrastructure, enabling deep optimization for large training runs.
- **Hacker Culture**: Rooted in the Noisebridge hackerspace values of do‑ocracy, low ego, and “be excellent to each other.”
- **Performance**: Rack‑scale NVIDIA systems (GB300, B200, H100) with high‑speed interconnects (NVIDIA Quantum‑2 InfiniBand).

## Strategic Focus
- Scaling infrastructure to support the next generation of superintelligence, including gigawatt‑scale AI factories.
- Enabling frontier labs to train trillion‑parameter models and serve billions of tokens in production.
- Expanding compliance and security capabilities for regulated industries.
- Growing the cloud platform (The Superintelligence Cloud) as the primary go‑to‑market offering.

## Why Work Here
- **Culture**: Hacker ethos (Noisebridge roots), low ego, no yelling, no politics, no crypto. Values: build, move fast, care, be excellent to each other.
- **Work Environment**: Fast‑paced, high‑change, outcome‑focused. Emphasis on technical excellence and curiosity. Anonymous feedback encouraged.
- **Interview Process**: Clear, structured steps (recruiter chat → hiring manager → technical assessment → panel interviews → reference/offer). Pedigree is not everything; focus on what you’ve built.
- **Location & Remote**: Offices in San Francisco and San Jose, CA. FAQ page addresses remote/hybrid policy (details not provided in available snippets); some roles appear on‑site.
- **Perks**: Benefits, time off, and other perks are listed on the careers site (specifics not extracted here).

## Sources
1. [lambda.ai/about](https://lambda.ai/about)
2. [lambda.ai/](https://lambda.ai/)
3. [lambda.ai/careers](https://lambda.ai/careers)
4. [lambda.ai/leadership](https://lambda.ai/leadership)

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