Senior Software Engineer - Core Cloud Platform

Posted Yesterday
Be an Early Applicant
2 Locations
Hybrid
296K-346K Annually
Senior level
Software
The Role
Build and operate core control-plane services for Lambda's GPU cloud: APIs, orchestration, schedulers, and bare-metal lifecycle workflows. Improve reliability, observability, testing, and on-call readiness; debug distributed production issues; collaborate across infrastructure, networking, fleet, security, and product teams; contribute design, code reviews, and mentoring.
Summary Generated by Built In

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/San Jose office location 4 days per week; Lambda’s designated work from home day is currently Tuesday.

About the Role

As a Senior Software Engineer on Lambda’s Core Cloud Platform team, you will build the control-plane systems that power Lambda’s GPU cloud. The team owns core platform capabilities across compute lifecycle, bare metal orchestration, maintenance actions, deployment readiness, reliability, and operational tooling.

You will work on systems that turn physical GPU infrastructure into reliable, customer-facing cloud capacity: APIs, workflows, orchestration layers, schedulers, and operational surfaces for instance lifecycle, host reclaim, validation, maintenance, and safe regional deployments.

This role is a strong fit for engineers who enjoy distributed systems, cloud infrastructure, operational excellence, and working close to the hardware/software boundary.

What You’ll Do

  • Build and operate core cloud platform services for compute lifecycle, bare metal hosts, capacity, placement, and maintenance workflows.

  • Design reliable APIs, backend services, state machines, and orchestration systems that power Lambda’s GPU cloud.

  • Work on bare metal lifecycle systems including launch, terminate, restart/reboot, host reclaim, validation, quarantine, and return-to-pool workflows.

  • Improve deployment, observability, testing, alerting, runbooks, and operational readiness for business-critical control-plane services.

  • Debug complex production issues across distributed services, infrastructure dependencies, networking, and cloud workflows.

  • Partner with infrastructure, networking, fleet, security, support, and product teams to define cross-system contracts and deliver end-to-end cloud capabilities.

  • Contribute to architecture, design docs, code reviews, incident follow-through, and mentoring across the team.

You May Be a Good Fit If You

  • Bachelor's degree or equivalent working experience.

  • Have 6+ years of professional software engineering experience building production backend or distributed systems.

  • Are strong in Python, Go, or a similar backend/system language.

  • Have experience designing and operating APIs, workflow engines, schedulers, orchestration services, or other distributed systems.

  • Understand reliability fundamentals: fault tolerance, idempotency, retries, state machines, failure handling, and production debugging.

  • Have experience with cloud or cloud-like infrastructure primitives such as compute, networking, storage, capacity management, identity, or fleet operations.

  • Are comfortable with Linux, containers, Kubernetes, infrastructure automation, and service deployment patterns.

  • Have owned production services, participated in on-call, and improved systems based on operational learnings.

  • Care about testability, CI/CD, observability, metrics, logging, alerting, and supportable operations.

  • Can take ambiguous infrastructure problems and drive them to clear designs, implementation plans, and production outcomes.

  • Communicate clearly across engineering, product, support, infrastructure teams, and leadership.

Nice-to-Haves

  • Experience building cloud control planes, compute platforms, schedulers, or infrastructure orchestration systems.

  • Experience with bare metal, GPU infrastructure, HPC, Kubernetes, Slurm, or large-scale AI/ML infrastructure.

  • Experience with host lifecycle, provisioning, validation, firmware, BMC/Redfish, fleet management, or maintenance workflows.

  • Familiarity with Temporal, Airflow, event-driven systems, or durable workflow orchestration.

  • Networking experience with VPCs, firewalls, SDN, InfiniBand, routing, or distributed systems networking.

  • Security-minded engineering experience, including identity, authorization, audit logging, attestation, or tenant isolation.

You Will Be Successful in This Role If You

  • Enjoy building foundational cloud systems where correctness, reliability, and operational clarity matter.

  • Are comfortable working across product, infrastructure, fleet, networking, security, and support boundaries.

  • Can break down ambiguous platform problems into concrete APIs, workflows, contracts, and implementation plans.

  • Care deeply about production behavior, not just code completion.

  • Move fast while maintaining high standards for reliability, testability, and supportability.

  • Communicate clearly and proactively, especially when risks, dependencies, or tradeoffs are unclear.

  • Want to help build the cloud platform layer for large-scale AI infrastructure.

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.

Skills Required

  • Bachelor's degree or equivalent experience
  • 6+ years professional software engineering experience building production backend or distributed systems
  • Proficiency in Python or Go (or similar backend/system language)
  • Experience designing and operating APIs, workflow engines, schedulers, orchestration services, or other distributed systems
  • Understanding of reliability fundamentals: fault tolerance, idempotency, retries, state machines, failure handling, production debugging
  • Experience with cloud or cloud-like infrastructure primitives: compute, networking, storage, capacity management, identity, or fleet operations
  • Comfortable with Linux, containers, Kubernetes, infrastructure automation, and service deployment patterns
  • Owned production services, participated in on-call, and improved systems based on operational learnings
  • Focus on testability, CI/CD, observability, metrics, logging, alerting, and supportable operations
  • Strong communication and collaboration across engineering, product, infrastructure, support, and leadership
  • Experience building cloud control planes, compute platforms, schedulers, or infrastructure orchestration systems
  • Experience with bare metal, GPU infrastructure, HPC, Kubernetes, Slurm, or large-scale AI/ML infrastructure
  • Experience with host lifecycle, provisioning, validation, firmware, BMC/Redfish, fleet management, or maintenance workflows
  • Familiarity with Temporal, Airflow, event-driven systems, or durable workflow orchestration
  • Networking experience with VPCs, firewalls, SDN, InfiniBand, routing, or distributed systems networking
  • Security-minded engineering experience including identity, authorization, audit logging, attestation, or tenant isolation

Lambda Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Lambda and has not been reviewed or approved by Lambda.

  • Fair & Transparent Compensation Pay is considered competitive for an AI infrastructure company, with posted ranges and observed offers indicating strong packages for senior technical roles. Compensation is often characterized as competitive or top‑shelf, aligning with market expectations.
  • Healthcare Strength Health, dental, and vision coverage are characterized as strong, with broad‑network plans noted and positive experiences highlighted. This foundation supports overall satisfaction with core insurance benefits.
  • Leave & Time Off Breadth Flexible or unlimited PTO is described as actually used, complemented by paid holidays and sick time. Generous parental leave examples further expand the time‑off offering.

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The Company
HQ: San Francisco, CA
106 Employees
Year Founded: 2012

What We Do

Lambda provides computation to accelerate human progress. We're a team of Deep Learning engineers building the world's best GPU workstations and servers. Our products power engineers and researchers at the forefront of human knowledge. Customers include Microsoft, MIT, Los Alamos National Lab, Disney, Tencent, Kaiser Permanente, Stanford, Harvard, Caltech, and the Department of Defense.

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