Top Engineering Jobs in Seattle, WA

Lead and grow a global team of Go developers building Kubernetes operators and automation for server fleet provisioning and lifecycle management. Set technical direction, prioritize work, and collaborate with hardware, fleet operations, and infrastructure teams. Establish onboarding, documentation, enablement, performance management, testing, deployment automation, observability, incident management, and reliability practices for large-scale fleet services.

Leads the Data Service Team, hiring and developing engineers while designing and operating scalable managed database services. Responsibilities include improving performance, security, reliability, and scalability; establishing data access standards; analyzing telemetry; ensuring regulatory compliance; and partnering with platform, product, and infrastructure teams. The role requires deep database, cloud-native, distributed systems, Kubernetes, observability, and reliability engineering expertise.

Lead the marimo engineering team across its open-source Python notebook ecosystem and molab cloud service. Manage and mentor engineers, guide architecture and technical direction, oversee staffing and releases, improve testing and CI/CD, and establish reliable production operations including observability, incident response, and capacity planning. The role also involves evaluating community contributions, translating user feedback into product improvements, and strengthening engineering practices as the team grows.

Design and implement distributed, exabyte-scale S3-compatible object storage for AI workloads. Improve storage reliability, durability, security, observability, throughput, and latency using technologies such as RDMA, GPU Direct Storage, and distributed filesystem protocols. Collaborate with infrastructure, platform, product, and operations teams to deploy and troubleshoot production systems, develop monitoring dashboards, analyze telemetry, and mentor engineers.

Develop and maintain scalable software for CoreWeave’s GPU infrastructure validation and performance testing platform. Build automated performance tests and hardware validation workflows, maintain Kubernetes controllers and operators, extend open-source tooling for system metrics and health visibility, troubleshoot infrastructure at scale, and participate in on-call support. The role requires Go or Python development and production-scale Kubernetes experience, with backend, hardware testing, HPC, and AI/ML infrastructure experience preferred.

Lead design of data center fit outs, ensuring compliance with project requirements and coordinating across teams. Manage projects from design through construction.

Lead electrical engineering design and delivery for hyperscale data center facilities. Develop scalable electrical infrastructure solutions, review consultant and contractor designs, validate electrical loads and system performance, conduct technical studies, ensure code compliance, and support testing, inspections, commissioning, troubleshooting, budgets, and schedules. Coordinate with consultants, vendors, IT, operations, mechanical, and project teams. Travel to various data center sites is required.

The posting identifies a Manager, Field Engineering role at CoreWeave, but does not provide specific responsibilities, qualifications, or team details. The position involves field engineering management in an AI cloud infrastructure environment. The role requires access to export-controlled information and may require U.S. person status or export authorization eligibility.

Support and maintain large-scale bare-metal GPU infrastructure across data centers. Diagnose customer issues and incidents, analyze logs across firmware, drivers, and hardware, coordinate data center interventions, troubleshoot networking, and participate in on-call operations. The role also develops automation, documentation, troubleshooting processes, and reliability improvements while collaborating with customers and engineering teams supporting HPC and AI workloads.

Design, build, and operate scalable multi-tenant file and block storage services for AI workloads. Own NFS and block data paths, Kubernetes CSI integration, control-plane capabilities, reliability, observability, security, and data protection. Develop provisioning, snapshots, quotas, encryption, and lifecycle management while partnering with infrastructure and platform teams. Mentor engineers and optimize high-performance distributed systems across CoreWeave’s storage fleet.