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Lambda

Cloud-based GPU services for AI training

Lead / Staff Full-Stack Software Engineer - Console Experience

Full-Stack EngineeringConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA

About the Job

Requirements

  • Extensive experience building and operating production web applications across the frontend and backend.
  • Experience leading the design and delivery of substantial customer-facing systems in a fast-moving environment.
  • High proficiency with modern frontend development, including React and TypeScript.
  • Ability to design and reason about APIs, service boundaries, data models, asynchronous workflows, and distributed-system failure modes.
  • Strong product judgment and care for usability, especially when presenting complex technical systems.
  • Ability to bring structure and momentum to ambiguous problems without waiting for every requirement to be defined.
  • Ability to communicate technical decisions clearly through design documents, diagrams, reviews, and direct collaboration.
  • Ability to build alignment across teams without relying on organizational authority.
  • Ability to balance short-term delivery with reliability, maintainability, and long-term architectural health.
  • Ability to take ownership of production outcomes, including testing, observability, incident response, and continuous improvement.
  • Invest in the growth and effectiveness of the engineers around you.

Responsibilities

  • Design, build, and operate end-to-end product experiences across the React and TypeScript frontend, APIs, and supporting backend services.
  • Own major console initiatives from early discovery and technical design through implementation, rollout, measurement, and iteration.
  • Translate complex cloud concepts—including compute lifecycle, networking, identity, governance, support, usage, and billing—into intuitive customer workflows.
  • Partner closely with Product and Design to clarify requirements, explore tradeoffs, and shape solutions that balance customer value with technical sustainability.
  • Collaborate with API Experience, Billing, Platform, and Support teams to deliver cohesive features spanning multiple systems.
  • Establish architectural patterns that improve frontend performance, reliability, accessibility, observability, and developer velocity.
  • Raise the engineering bar through thoughtful design reviews, code reviews, documentation, testing, and operational ownership.
  • Identify recurring friction in the product and codebase, then lead durable improvements rather than isolated fixes.
  • Mentor engineers and help teammates develop stronger product, architecture, and execution skills.
  • Contribute to roadmap planning and technical strategy for the Console Experience team.
  • At the Lead Engineer level, own the technical delivery of significant, ambiguous product areas; coordinate execution across several engineers and partner teams; make architectural decisions within the Console Experience domain; and improve team practices while mentoring engineers through hands-on technical leadership.
  • At the Staff Engineer level, set technical direction across multiple product areas or teams; lead multi-quarter initiatives with broad architectural and organizational impact; align teams around shared interfaces, patterns, and long-term platform investments; anticipate systemic risks and opportunities while influencing roadmaps beyond the immediate team; and serve as a trusted technical partner to engineering, product, and design leadership.

Desired Qualifications

  • Experience building a cloud console, infrastructure product, or enterprise SaaS application.
  • Familiarity with GPU infrastructure, Kubernetes, networking, identity and access management, or cloud control planes.
  • Experience evolving a frontend architecture or design system across multiple teams.

About the Company

Lambda

Cloud-based GPU services for AI training

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.

Company size
501-1,000
Company stage
Late Stage VC
Total funding
$9.1B
Headquarters
San Jose, CA
Founded
2012

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