--- title: 'Technical Success Engineer at Lambda' canonical: 'https://feeny.ai/job/technical-success-engineer-lambda-san-francisco-hf8nmn6q0gwq' type: 'job' last_seen: '2026-09-06' --- # Technical Success Engineer at Lambda - **Company:** Lambda - **Location:** San Francisco, CA - **Employment:** full-time - **Work type:** hybrid - **Posted:** 2026-08-20 - **Last confirmed live:** 2026-09-06 - **Apply:** https://jobs.ashbyhq.com/lambda/2b7fbb56-fc5b-4d9d-91a6-fdfb81a135e8 ## 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 San Jose office location 4 days per week; Lambda’s designated work from home day is currently Tuesday. ## About this role The Superintelligence Technical Success Engineer is part of Lambda's Superintelligence business unit, dedicated to our largest, most strategic customers operating in the most complex environments. This role owns taking signed deployment from contract to a live, fully operational production environment. The role requires strong technical acumen to validate the build against what was promised, spot gaps, and work effectively with engineering and infrastructure teams to get issues resolved and requirements clearly understood. You'll work alongside the account team, to make sure the customer's requirements and expectations are clearly understood and addressed throughout deployment. This role calls for someone who's ready to dive in wherever the engagement needs them. ## What You'll Do - Take signed deployments, from contract, to live, to working production environments, validating configuration, connectivity, storage, and compute against what was promised - Bring technical depth to validation and troubleshooting conversations — asking the right questions, spotting gaps, and working closely with engineering and infrastructure teams to drive issues to resolution - Coordinate with Infrastructure, Engineering, Product, and Data Center teams to close technical dependencies and resolve blockers - Own a current, accurate technical picture of the deployment — what's built, what's open, what's at risk - Keep stakeholders informed with clear, regular status updates: RAG status, top risks, and what's being done about them - Guide the customer through onboarding to their first successful production workload - Be the customer's go-to technical contact through deployment and early production - Feed recurring technical patterns back into reusable runbooks, checklists, or automation - Transition out once the customer is stable and self-sufficient, keeping the broader account team informed along the way You - 4+ years of hands-on technical experience with GPU/HPC infrastructure, cloud platforms, Kubernetes, or large-scale Linux systems - Comfortable being the technical voice in the room able to validate builds, spot gaps, and hold engineering teams accountable for resolving them - Strong troubleshooting instincts and a willingness to get into the weeds of networking, storage, or compute issues - Track record of coordinating across engineering and infrastructure teams to close out technical dependencies - Clear written and verbal communication for status updates and technical documentation - A bias toward diving in and taking ownership, rather than waiting for a fully defined process ## Nice to Have - Exposure to large-scale GPU cluster deployments - Familiarity with project/program tracking tools and structured status reporting - Experience building runbooks or checklists that outlived the engagement they were built for 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 - [Staff Data Center Implementation Manager](https://feeny.ai/job/staff-data-center-implementation-manager-lambda-united-states-jyfexyg9by63) — United States - [Senior Manager, Detection and Response](https://feeny.ai/job/senior-manager-detection-and-response-lambda-bellevue-f6jvw1b07xwk) — Bellevue, WA - [Data Center Construction Site Foreman (Dallas)](https://feeny.ai/job/data-center-construction-site-foreman-dallas-lambda-united-states-vc7fg15nb275) — United States - [Construction Administrator](https://feeny.ai/job/construction-administrator-lambda-san-jose-ky6swv0mtr9v) — San Jose, CA - [Commodity Sourcing Manager – AI Infrastructure](https://feeny.ai/job/commodity-sourcing-manager-ai-infrastructure-lambda-san-jose-9zfy7qfg5bw5) — San Jose, CA - [Data Center Operations Systems Engineer (San Jose)](https://feeny.ai/job/data-center-operations-systems-engineer-san-jose-lambda-san-jose-qabp07hbyq33) — San Jose, CA - [Senior Software Engineer - Compute](https://feeny.ai/job/senior-software-engineer-compute-lambda-san-francisco-py5yr29fwf6a) — San Francisco, CA - [Senior Site Reliability Engineer - Fleet](https://feeny.ai/job/senior-site-reliability-engineer-fleet-lambda-san-francisco-33fy0znbk8rz) — San Francisco, CA - [Technical Account Manager](https://feeny.ai/job/technical-account-manager-lambda-san-francisco-9vfyd226yv92) — San Francisco, CA - [Technical Product Marketing Manager - Public Cloud](https://feeny.ai/job/technical-product-marketing-manager-public-cloud-lambda-san-jose-hcrgg2jy9v1d) — San Jose, CA