--- title: 'Network Planning & Design Manager at Lambda' canonical: 'https://feeny.ai/job/network-planning-design-manager-lambda-san-francisco-y6e7f7epjkxy' type: 'job' last_seen: '2026-10-18' --- # Network Planning & Design Manager at Lambda - **Company:** Lambda - **Location:** San Francisco, CA - **Employment:** full-time - **Work type:** hybrid - **Posted:** 2026-10-09 - **Last confirmed live:** 2026-10-18 - **Apply:** https://jobs.ashbyhq.com/lambda/3853bc6e-a75d-417e-8fd0-ae5446c44e1e ## 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 or Bellevue office location 4 days per week; Lambda’s designated work from home day is currently Tuesday. ## About the Role Design the connectivity behind Lambda’s next data center, backbone route and customer interconnect. You’ll work directly with carrier engineers and equipment partners to turn capacity, latency and resilience requirements into infrastructure we can build. Our customers are building AI training and inference systems that depend on moving data to and between compute sites. Your decisions about routes, carrier reach and future capacity will help determine how that network grows. This is a technical individual contributor role on the Network Planning and Delivery team within Cloud and AI Networking. You’ll take designs through Network Engineering approval and stay involved as our Delivery Managers and suppliers put them into service. You’ll see your designs become working infrastructure and help set the standards for what we build next. ## What You’ll Do Design the Network - Develop physical and optical connectivity designs for data centers, points of presence, backbone routes and customer interconnects. - Translate customer and network requirements into routes, capacity plans, equipment needs and acceptance criteria, working within Network Engineering’s and HPC architecture. - Compare dark fiber, wavelength, internet transit and interconnection options on latency, resilience, total cost, delivery time and room for expansion. - Validate route diversity and identify shared conduits, building entrances, fiber extensions and other dependencies that could compromise a design. Develop Solutions with Suppliers - Work with carrier engineering teams to develop routes, extend reach and resolve coverage, site access or capacity constraints. - Evaluate new and existing suppliers, gather technical proposals and budgetary quotes, and recommend options with clear tradeoffs. - Work with optical and network equipment partners on alternatives when fiber availability, equipment lead times or cost put a build at risk. - Give Supply Chain a defined technical scope for negotiations and contracting, including supplier assumptions and unresolved risks. Take Designs into Delivery - Produce a complete design package for Network Engineering approval, then work with Delivery on the build schedule, dependencies and acceptance requirements. - Resolve design questions during delivery and take revisions back through Network Engineering review when site or supplier conditions change. - Work with Site Selection and network planning on carrier access, backbone capacity and future expansion before deployment dates are committed. - Turn lessons from completed projects into reusable designs and standards with Network Engineering. You - Experience designing or developing carrier, cloud or data center connectivity, with designs that have progressed from requirements into delivery. - Practical knowledge of dark fiber, wavelength services, optical transport and internet interconnection. - Ability to assess physical route diversity, equipment dependencies and capacity needs beyond what a route map alone shows. - Experience working directly with carrier engineers, colocation providers or equipment suppliers to solve design constraints. - Ability to compare supplier options on technical fit, delivery risk and total cost, and explain your recommendation. - Clear design documentation that engineering reviewers and delivery teams can use. ## Nice To Have - Experience designing long-haul optical networks or dense wavelength division multiplexing (DWDM) systems. - Experience with private cloud connectivity, internet exchanges or large compute deployments. - Carrier solutions engineering experience, or familiarity with route mapping and capacity planning tools. We Are Looking for Someone Who Is - Curious enough to investigate how a proposed route will work in the field. - Comfortable making a recommendation, explaining the assumptions and revising it when the facts change. - Motivated by seeing your designs built and improving how the next project gets done. 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) ## Other roles at Lambda - [Senior Finance Systems Architect](https://feeny.ai/job/senior-finance-systems-architect-lambda-san-francisco-xm8j0m2v06c8) — San Francisco, CA - [Senior Analyst - Investor Relations](https://feeny.ai/job/senior-analyst-investor-relations-lambda-san-francisco-k9fx1taykgcb) — San Francisco, CA - [Principal Product Manager - Console](https://feeny.ai/job/principal-product-manager-console-lambda-bellevue-grhs8jsg305p) — Bellevue, WA - [Lead / Staff Full-Stack Software Engineer - Console Experience](https://feeny.ai/job/lead-staff-full-stack-software-engineer-console-experience-lambda-san-francisco-5vc6y6f42h61) — San Francisco, CA - [Controller](https://feeny.ai/job/controller-lambda-san-jose-6aq9p2xm7a59) — San Jose, CA - [Head of Tax](https://feeny.ai/job/head-of-tax-lambda-san-francisco-w2mk4rcpsp9w) — San Francisco, CA - [Staff Product Manager - Observability](https://feeny.ai/job/staff-product-manager-observability-lambda-bellevue-5t09nw1b5snq) — Bellevue, WA - [Technical Program Manager - Data Center Infrastructure Delivery](https://feeny.ai/job/technical-program-manager-data-center-infrastructure-delivery-lambda-united-4ke422t8s71r) — United States - [Network Infrastructure Delivery Manager](https://feeny.ai/job/network-infrastructure-delivery-manager-lambda-san-francisco-8xzaptr7xkjt) — San Francisco, CA - [Network Analyst](https://feeny.ai/job/network-analyst-lambda-san-francisco-789ycevmdbne) — San Francisco, CA