Senior Systems Engineer
Lambda
Senior Systems Engineer
Lambda
Cloud-based GPU services for AI training
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 of San Jose office location 4 days per week; Lambda's designated work from home day is currently Tuesday
Information Systems at Lambda is responsible for building and scaling the internal systems that power our business. We partner across the company—Finance, GTM, Engineering, and People—to implement tools, automate workflows, and ensure data flows securely and accurately. Our scope includes enterprise applications, integrations, data platform and analytics, compliance automation, and all things IT.
What You’ll Do
Design, write, and deliver software and services to improve the availability, scalability, reliability, and efficiency of Lambda’s internal IT systems and platforms.
Solve problems relating to mission critical services and build automation to prevent problem recurrence with the goal of automating response to all non-exceptional events.
Work with Lambda Engineering and internal teams to Influence and create new designs, architectures, standards, and methods for large-scale distributed systems.
Engage in service capacity planning and demand forecasting, software performance analysis, and system tuning.
Be an excellent communicator, producing documentation and related artifacts for the systems you are responsible for.
You
6+ years in software engineering, site reliability engineering, or IT systems engineering where you built and ran things in code, not just configured them.
Build & Scale Internal AI Tooling: Design and deploy low-code/no-code and custom internal platforms (using tools like Appsmith, custom Vercel-hosted frontends, etc.) integrated with LLM workflows to automate daily IT and operationalize similar work for Lambda users.
Manage AI Infrastructure & Gateways: Deploy, monitor, and optimize internal AI proxy gateways to route model traffic, manage API rate limits, optimize latency, and control inference costs across teams.
Automate Operational Pipelines: Integrate AI agents into internal IT workflows (Slack/Discord bots, incident triage, log parsing via Datadog, user provisioning, ticket routing).
Maintain and Monitor Platform Health & CI/CD: Manage deployments, serverless functions, and infra pipelines (Vercel, AWS/GCP, etc) to ensure 99.9% uptime for all internal systems.
Governance & Security: Implement guardrails, data-privacy controls, and secret management to ensure sensitive corporate data isn't exposed to third-party LLM providers.
Have an urge to collaborate and communicate asynchronously, combined with a desire to record and document issues and solutions.
Have an enthusiastic, go-for-it attitude. When you see something broken, you can’t help but fix it.
Have an urge for delivering quickly and effectively, and iterating fast.
Nice to Have
Experience and interest in ML/AI workloads and compute
Practical experience implementing and managing paging, alerting, and on-call scheduling flows
A positive attitude, combined with a desire to learn and collaborate
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.
Lambda Labs provides cloud-based GPU services for AI training and inference via its AI Developer Cloud, powered by NVIDIA GH200 Grace Hopper hardware to efficiently train large language models and generative AI. Customers access on-demand or reserved GPUs and are billed by the hour (for example, NVIDIA H100 at about $1.99/hour); it also offers Lambda Echelon, where clients own infrastructure but pay a monthly hosting and support fee, and Lambda Stack, a software suite that helps ML teams install and upgrade tools like PyTorch, TensorFlow, CUDA, cuDNN, and NVIDIA drivers. The company differentiates itself through competitive pricing, available high-end hardware, and an integrated ML software stack that streamlines workflows. Its goal is to enable scalable, affordable AI development and deployment by providing flexible GPU access, reliable hosting, and easy software deployment for teams working with large models.
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