---
title: 'Director, Network Capacity Automation at Lambda'
canonical: 'https://feeny.ai/job/director-network-capacity-automation-lambda-bellevue-fyktn50b3wpw'
type: 'job'
last_seen: '2026-09-13'
---

# Director, Network Capacity Automation at Lambda

- **Company:** Lambda
- **Location:** Bellevue, WA
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-09-11
- **Last confirmed live:** 2026-09-13
- **Apply:** https://jobs.ashbyhq.com/lambda/dce516d5-2e8e-4bc1-970c-ad7c0c222674

## 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 Bellevue or San Francisco office location 4 days per week; Lambda’s designated work from home day is currently Tuesday.

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. Our vision is bold and is not an incremental exercise. We will continually re-evaluate and reinvent our current ways of working and the automation underneath all of it, while operating the existing network flawlessly for all customer workloads. Lambda has 10x'd over the last three years, and the network engineering organization is scaling to match. We're looking for a Director of Network Capacity Automation to lead one or more teams building the software that enables us to plan and deliver network capacity ahead of customer demand. This capacity is critical to ensure a flawless customer connectivity experience to our GPU cloud infrastructure. We're looking for a Director to own that outcome end to end — and to build the organization that delivers it. You'll hire and grow a talented team of software and network proficient engineers, shape team culture, and partner with technical leadership to deliver the mechanisms needed to stay ahead of our scale ambitions. This role will report to the VP of Cloud and AI Networking, working alongside a highly capable and passionate team of engineers. If you'd like to join a great team of customer obsessed engineers building the world's best AI cloud, come join us.

## What You'll Do

- Own network capacity end to end — planning, delivery, turn-up and lifecycle — and be accountable for capacity landing ahead of demand
- Build and lead the organization that delivers it: hire, develop and retain engineers and the leaders who manage them, and design the team structure as the org grows
- Set the multi-year technical strategy for capacity automation to ensure it continually scales
- Convert manual process into durable software — the goal is a capacity pipeline that runs without heroics, not a better-organised set of runbooks
- Own the operational bar for your org: how capacity work is planned, reviewed, shipped, measured and learned from when it goes wrong
- Manage through leads and senior ICs, developing both — regular 1:1s, clear performance feedback, growth planning, and sponsorship of meaningful work
- Partner and support our Interconnect team who negotiate, acquire and coordinate on external connectivity
- Partner with Principal Engineers and technical leadership to maintain a high engineering bar across design, code quality and operational reliability
- Partner with Infrastructure, Supply Chain, Data Center Operations, Product and Finance to align capacity roadmaps, forecast demand and manage long-lead dependencies
- Represent your org's work and technical direction to senior leadership, and to enterprise customers and partners where appropriate
- Contribute to org-wide engineering process improvements — how we plan, how we ship, how we learn from incidents

You

- Have 8+ years of engineering management experience, including directly managing senior individual contributors
- Proven track record of building and scaling engineering organizations that deliver mission-critical, high-performance cloud connectivity serving millions of users
- Have a software engineering background — you've shipped production systems and can engage credibly on architecture, technical tradeoffs, and code quality
- Foster a data driven, automation first, high velocity organization
- Familiarity designing, building, scaling and operating large-scale networks
- Familiarity with how to build distributed systems and large-scale networking services
- Strong automation skills and track record accelerating a business delivery velocity on a large scale
- Have a track record of building high-performing teams in fast-moving, technically demanding environments
- Are skilled at translating ambiguous business and product goals into clear team priorities and executable engineering plans
- Show strong judgment about when to go deep technically, when to delegate, and when to escalate
- Track record of successful project and product delivery in fast-paced, high-pressure environments
- Excellent communicator both written and verbal. You leverage high quality written artifacts to inform high quality decision making and get approval on problems and solution opportunities

## Nice to Have

- Experience in GPU cloud, HPC, or AI/ML infrastructure environments
- Deep familiarity with large-scale data center or cloud networking — fabric build-out, capacity modelling, or network supply chain
- Experience with infrastructure capacity forecasting and long-lead hardware planning
- Prior experience at a high-growth infrastructure or cloud company

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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