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 office four days per week. Lambda’s designated work-from-home day is currently Tuesday.

About the Role

Lambda’s Cloud Console is where customers discover, provision, and manage the infrastructure behind their AI workloads. Through the console, customers manage GPUs and clusters, configure networking and identity, monitor usage and billing, and navigate increasingly sophisticated enterprise workflows.

We are looking for a Lead or Staff Full-Stack Software Engineer to help define and build the next generation of this experience. You will own complex, customer-facing initiatives across the frontend, API, and service layers while helping the team establish scalable architecture and strong engineering practices.

This is a high-impact individual-contributor role for an engineer who combines product judgment with technical depth. You will work closely with Product and Design, partner with teams across the cloud platform, and turn complex infrastructure capabilities into UI and workflows that feel clear, reliable, and cohesive.

We are open to hiring at the Lead or Staff level. Level and scope will be determined by a candidate’s experience and demonstrated impact.

What You’ll Do

Design, build, and operate end-to-end product experiences across our 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 our 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

Scope by Level

At the Lead Engineer level, you will typically:

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

Improve team practices and mentor engineers through hands-on technical leadership

At the Staff Engineer level, you will additionally:

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, influencing roadmaps beyond the immediate team

Serve as a trusted technical partner to engineering, product, and design leadership

You

Have extensive experience building and operating production web applications across the frontend and backend

Have led the design and delivery of substantial customer-facing systems in a fast-moving environment

Are highly proficient with modern frontend development, including React and TypeScript

Can design and reason about APIs, service boundaries, data models, asynchronous workflows, and distributed-system failure modes