Engineering Manager, Core Cloud Platform & Kubernetes

Lambda; San Jose (CA); Hybrid; USD 180,000 - 260,000; Full time

Benefits offered by this job

Health/dental/vision coverage

Wellness stipends

Commuter stipends

401k with 2% company match

Job summary

Lambda is seeking an Engineering Manager to lead a team building and running foundational cloud-platform services. You will own the team’s people, execution, quality, and production outcomes while guiding senior engineers on technical direction.

This role sits in Lambda’s Core Cloud Platform, focusing on evolving the Managed Kubernetes platform and ensuring scalability for AI workloads. You will collaborate with senior staff to shape architecture and delivery across distributed systems.

Qualifications

• 4+ years of engineering management experience with a track record of growing high-performing teams.
• 7+ years of software engineering IC experience in mission-critical distributed systems.
• 8+ years implementing business-critical services in Python or Go.
• Experience coordinating across compute, networking, and storage without owning them directly.
• Background in multi-region deployment, cross-datacenter state management, and high-availability architectures.
• Strong track record of owning projects end-to-end: architecture, delivery, operations.

Responsibilities

• Lead design, implementation, and production operation of foundational cloud-platform services.
• Own the technical roadmap for a more distributed, resilient, observable platform.
• Ensure reliable operation across multi-datacenter and multi-region fleet.

Skills

Engineering management

Distributed systems

Python/Go

Cross-functional collaboration

Kubernetes

Job description

Lambda is seeking an Engineering Manager to lead a team building and running foundational cloud-platform services. You will own the team’s people, execution, quality, and production outcomes while guiding senior engineers on technical direction.

This role sits in Lambda’s Core Cloud Platform, focusing on evolving the Managed Kubernetes platform and ensuring scalability for AI workloads. You will collaborate with senior staff to shape architecture and delivery across distributed systems.