L

Lambda

Cloud-based GPU services for AI training

Data Center Standards Architect

Full-TimeUpdated on 10/4/2026
$443k - $590k/yr+ Equity compensation + 401(k) match of 2%
Expert
San Jose, CA, USA
HybridFour days per week in the San Francisco office; Tuesday is currently the work-from-home day.

About the job

Requirements
  • Have operated as a staff, principal, or director-level engineering leader in data center engineering, infrastructure engineering, facilities engineering, cloud infrastructure, hardware infrastructure, or a related technical domain.
  • Have experience designing or scaling standards, processes, tools, or governance systems across a complex engineering organization.
  • Bring a strong systems-thinking mindset and be comfortable turning ambiguous, one-off problems into repeatable, scalable mechanisms.
  • Have deep familiarity with data center infrastructure, including power, cooling, rack layouts, network infrastructure, cabling, commissioning, operational readiness, and lifecycle management.
  • Understand how to balance engineering excellence with delivery velocity, cost, risk, reliability, and operational simplicity.
  • Be comfortable influencing without direct authority across engineering, operations, construction, supply chain, finance, and executive stakeholders.
  • Communicate clearly through written standards, technical narratives, architecture diagrams, design reviews, and executive-level recommendations.
  • Have a track record of raising the technical bar for teams through better processes, documentation, decision-making frameworks, and engineering discipline.
  • Care deeply about reliability, maintainability, repeatability, and operational excellence in mission-critical infrastructure environments.
Responsibilities
  • Define and own Lambda’s data center engineering standards for high-density AI and GPU infrastructure environments.
  • Create repeatable reference architectures, design patterns, technical specifications, and deployment standards that improve speed, quality, reliability, and consistency across data center builds.
  • Develop the engineering operating system for data center scale, including standards libraries, design review processes, decision records, quality gates, commissioning criteria, acceptance checklists, exception processes, and operational handoff frameworks.
  • Translate lessons learned from individual deployments into reusable mechanisms that make future deployments safer, faster, and more predictable.
  • Establish technical standards across power distribution, cooling, liquid cooling readiness, rack integration, structured cabling, fiber management, network rooms, out-of-band management, telemetry, DCIM/BMS integrations, physical security, maintainability, and operational readiness.
  • Lead cross-functional architecture reviews for new data center designs, expansions, retrofits, and infrastructure programs.
  • Identify organizational bottlenecks and design systems, tools, and workflows that reduce ambiguity, improve accountability, and help teams execute at scale.
  • Build governance mechanisms for standards adoption, including exception management, risk reviews, lifecycle ownership, metrics, and continuous improvement loops.
  • Act as a technical advisor to senior engineering and infrastructure leadership on data center strategy, design tradeoffs, resiliency, operational risk, and scalability.
  • Mentor engineers and technical leaders across the organization by raising the bar for systems thinking, documentation, design rigor, and operational excellence.
Desired Qualifications
  • Experience with AI, machine learning, GPU, high-performance computing, or hyperscale cloud infrastructure.
  • Experience with high-density compute environments, liquid cooling, advanced thermal management, or next-generation data center design.
  • Experience building or operating infrastructure standards across multiple sites, regions, colocation providers, or global data center portfolios.
  • Familiarity with data center infrastructure management, building management systems, electrical power monitoring systems, telemetry platforms, infrastructure observability, or workflow automation tools.
  • Experience creating internal platforms, tooling, dashboards, or knowledge systems that help engineering organizations scale.
  • Experience working with colocation providers, original equipment manufacturers, original design manufacturers, construction partners, commissioning agents, and critical facilities operations teams.
  • Experience leading technical governance forums, architecture review boards, standards councils, or large-scale engineering transformation programs.
  • Background in electrical engineering, mechanical engineering, systems engineering, network engineering, infrastructure architecture, or a related field.

About the company

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

Late Stage VC

Total Funding

$8.1B

Headquarters

San Jose, California

Founded

2012

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Simplify's Take

What believers are saying

  • October 1, 2026, Lambda closed $1 billion fixed-rate debt for contracted deployments.
  • August 31, 2026 Reuters reported Anthropic's $35 billion Lambda deal for Texas capacity.
  • May 2026 leadership changes installed Michel Combes and John Donovan for scale execution.

What critics are saying

  • Lambda's growth now depends on Nvidia chip allocation and pricing, tightening margins immediately.
  • October 1 financing secures three deployments; one canceled off-take strains highly levered infrastructure economics.
  • A failed hyperscale customer ramp, especially Anthropic, threatens refinancing and a pre-IPO exit.

What makes Lambda unique

  • Lambda pairs bare-metal GPU clouds with on-prem hardware and software, simplifying full-stack AI deployment.
  • At GTC 2026, Lambda announced early Vera Rubin NVL72 bare-metal instances for H2 2026.
  • Lambda runs production-scale infrastructure, including Quantum-X InfiniBand Photonics on 10,000-GPU GB300 clusters.

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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

↑ 0%

1 year growth

↑ 2%

2 year growth

↑ 1%
Yahoo Finance
Sep 1st, 2026
Anthropic signs $35B cloud deal with Nvidia-backed Lambda for Texas data centre

Anthropic has signed a $35 billion cloud-computing agreement with Nvidia-backed Lambda, the Wall Street Journal reported. The deal gives Anthropic access to computing capacity from a Texas data centre being developed by Hut 8, a Bitcoin miner turned data centre operator. Nvidia secured capacity at the facility, whilst Lambda will deploy Nvidia chips and provide computing resources to Anthropic. The arrangement's financial terms remain unclear. Anthropic's annualised revenue run rate reportedly reached $65 billion by end-July. The structure highlights Nvidia's expanding role beyond selling AI chips. Anthropic previously agreed to spend $45 billion over six years with another Nvidia-backed provider, Nscale. In April, Amazon announced Anthropic plans to spend over $100 billion on AWS technology over the next decade.

Associated Press
Aug 27th, 2026
Lambda closes $926M term loan B to fund GPU infrastructure for investment-grade customer

Lambda has closed a $926 million senior secured term loan B facility to fund GPU infrastructure for an investment-grade customer. The facility, priced at SOFR + 3.00% and issued at 99.5% of principal, received a Baa2 rating from Moody's. This marks Lambda's first large-scale private cloud GPU asset-backed financing and the first broadly syndicated, investment-grade-rated term loan B by a private neocloud. The facility matures on 31 December 2030 and is secured by the GPU servers and related infrastructure it funds. The closing follows Lambda's $1 billion senior secured credit facility announced in May 2026. Morgan Stanley acted as lead left arranger, bookrunner, and administrative agent, with MUFG serving as joint bookrunner.

The Next Web
Aug 25th, 2026
Lambda is raising up to $3bn before an IPO, months after borrowing $917m for chips

Nvidia-backed Lambda is in talks for up to $3bn in pre-IPO financing at a valuation of $12bn or more, ahead of a listing next year.

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.