Senior Software Engineer – Core Cloud Platform

Lambda

. Design, build, and operate services, APIs, control planes, and platform capabilities powering Lambda’s AI cloud .

Posted 9/25/2026full-timeUnited StatesSenior💰 $230,000 - $346,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing, building, and operating distributed systems and cloud services, with a strong focus on performance, reliability, and security. Proven ability to lead cross-functional collaboration and drive engineering improvements through automation and best practices.

Highest-signal resume keywords

Go Programming LanguagePython Programming LanguageKubernetesCloud Services on AWS, GCP, AzureDistributed Systems Design

ATS Keywords

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Hard Skills

Software EngineeringBackend Services DevelopmentInfrastructure AutomationEvent-Driven ArchitecturesSystem DesignConcurrency ReasoningError HandlingTestingPerformance OptimizationProduction Reliability

Soft Skills

Cross-Functional CollaborationMentorshipConsensus Building

Tools & Technologies

Cloud Control-Plane SystemsContainer OrchestrationDurable Workflow SystemsIdentity and Access ManagementUsage Metering and Billing

Industry Keywords

AI CloudGPU InfrastructureHPC EnvironmentsLarge-Scale AI/ML TrainingProduction Systems

Tech Stack

Tools & technologies

AWSAzureCloudDistributed SystemsGoogle Cloud PlatformKubernetesPythonGo

About the role

Key responsibilities & impact

Design, build, and operate services, APIs, control planes, and platform capabilities powering Lambda’s AI cloud
Solve distributed-systems problems involving state, consistency, concurrency, scheduling, failure recovery, and safe lifecycle management
Own the full engineering lifecycle from problem framing and architecture through implementation, testing, rollout, observability, on-call, and continuous improvement
Improve system availability, latency, throughput, efficiency, security, and operability as Lambda scales
Convert incidents and near misses into durable engineering improvements, including automation, testing, guardrails, and backstops
Collaborate with product, infrastructure, networking, storage, security, and SRE teams to resolve dependencies and deliver customer outcomes
Use AI-assisted development tools while independently verifying correctness, security, and maintainability
Contribute to technical standards, design and code reviews, and mentorship
At Staff level, lead cross-team architecture and raise the organization’s technical capabilities
Operate distributed systems powering Lambda’s GPU cloud, including compute control planes, managed Kubernetes, cloud APIs, identity and access, usage metering and billing, capacity and orchestration, reliability, and developer-facing infrastructure

Requirements

What you’ll need

7 or more years of professional software engineering experience, or equivalent evidence of impact building production systems
Depth in at least one general-purpose programming language; Lambda primarily works in Go and Python
Ability to reason about concurrency, error handling, and testing
Experience designing, building, and operating backend services, distributed systems, infrastructure, or platform capabilities at meaningful scale
Practical understanding of system design, data models, APIs, failure modes, performance, and production reliability tradeoffs
Track record of owning complex work through delivery and operation, including testing, staged rollout, monitoring, incident response, and root-cause improvement
Proven track record of aligning cross-functional partners and gaining consensus around decisions and tradeoffs
Experience building cloud services or platform infrastructure, or operating large-scale production systems on AWS, GCP, Azure, or a comparable cloud platform
Experience with Kubernetes, container orchestration, schedulers, controllers, or cloud control-plane systems
Experience in cloud infrastructure or platform domains such as compute, storage, networking, identity and access, developer platforms, usage metering and billing, databases, or fleet management
Experience with infrastructure automation, durable workflow systems, event-driven architectures, or infrastructure as code
Experience designing highly available, multi-region, or rapidly scaling distributed systems
Familiarity with GPU infrastructure, HPC environments, or large-scale AI/ML training and inference workloads
Must be able and willing to work onsite at the San Francisco office 4 days a week
Must be legally authorized to work in the United States; visa sponsorship may be available

Benefits

Comp & perks

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
AI interview recording opt-out without impact on candidacy