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Lambda is building the world's leading AI cloud infrastructure platform, serving tens of thousands of customers from AI researchers to enterprises and hyperscalers. The Core Cloud Platform organization is responsible for the foundational software and services that transform large-scale GPU infrastructure into reliable, customer-facing cloud products.
As Engineering Manager for Core Cloud Platform, you will lead a team building and operating foundational platform services including Managed Kubernetes, resource lifecycle management, workload orchestration, cloud APIs, automation, observability, and multi-region operations. Your immediate focus includes evolving Lambda's Managed Kubernetes platform to make it easier and safer to provision, upgrade, operate, and scale Kubernetes clusters for demanding AI workloads.
You will own the team's people development, execution, technical quality, and production outcomes. This is a high-leverage role at the intersection of cloud infrastructure, distributed systems, Kubernetes, and customer experience.
Key responsibilities include:
- Leading the design, implementation, and production operation of foundational cloud-platform services
- Owning the technical roadmap for making the platform more distributed, resilient, observable, and operationally efficient
- Ensuring reliable multi-datacenter and multi-region operations with appropriate handling of partial failures and long-running workflows
- Partnering with senior and staff engineers on sound architectural decisions across distributed services, stateful systems, APIs, schedulers, controllers, and automation
- Defining clear contracts and integration patterns between cloud platform and compute, networking, fleet, security, and customer-facing systems
- Leading and growing a team of senior and staff engineers; hiring, developing talent, maintaining high performance standards
- Owning project planning, prioritization, and delivery aligned with business objectives and customer commitments
- Establishing strong engineering practices including design reviews, testing, CI/CD, observability, incident response, and on-call operations
- Collaborating with peer Engineering Managers and cross-functional partners to resolve dependencies
- Improving engineering leverage through automation and responsible AI-assisted engineering
- Staying current with Kubernetes, cloud-native infrastructure, GPU orchestration, and platform automation developments
Requirements:
- 4+ years of engineering management experience with demonstrated track record of growing high-performing teams
- 7+ years of software engineering IC experience, including principal or staff-level ownership of mission-critical distributed systems
- 8+ years implementing business-critical services in Python or Go, from conception through production
- Experience building systems that coordinate across multiple independently-owned infrastructure services (compute, networking, storage) without owning them directly
- Background in multi-region deployment strategies, cross-datacenter state management, and high-availability architectures
- Strong track record of owning projects end-to-end: architecture, delivery, operations, and continuous improvement
- Excellent cross-functional collaboration and proven ability to drive alignment across infrastructure, platform, and product teams
Nice to Have:
- Awareness of bare metal and GPU infrastructure ecosystem, including NVIDIA NiCo, BlueField DPU capabilities, and industry standards for multi-tenant bare metal management
- Experience evaluating or adopting vendor infrastructure tooling into existing platforms
- Familiarity with Kubernetes or Slurm
- Experience in AI, ML, or GPU hardware industry
- Proven track record designing large-scale cloud IaaS platforms from the ground up
- Exposure to IPO readiness, enterprise compliance, or security requirements at scale
Note: This position requires presence in San Francisco, San Jose, or Bellevue office 4 days per week; Tuesday is Lambda's designated work-from-home day.
