Top Engineering Jobs in Seattle, WA

Design, validate, and optimize power delivery systems and collaborate with teams to enhance hardware designs for AI data centers.

The Production Engineer will design and maintain support tools, develop AI-driven solutions, and partner with teams to enhance customer experience and operational reliability.

Design, deploy, and maintain SOAR capabilities for security automation, develop workflows, and integrate AI tooling for enhanced security responses.

The Senior Software Engineer will design and build secure sandboxed runtime environments for Kubernetes, focusing on GPU workloads and ensuring performance and security in multi-tenant configurations.

The Staff Frontend Engineer will design the UI for a high-performance datacenter infrastructure platform, optimizing for speed and handling complex datasets. Responsibilities include building applications, collaborating on API design, and establishing frontend architecture.

The Senior Software Engineer will develop and maintain the marimo open-source notebook, focusing on backend design, library development, and community engagement.

Own, build, and operate production reliability tooling and systems across the cloud stack. Lead projects to improve availability, scalability, automation, observability, and incident response. Ship production services in Python/Go, participate on-call, reduce toil through automation, and maintain long-lived platform frameworks.

Lead end-to-end technical delivery of large-scale bare-metal GPU clusters for strategic customers: facility/rack design, GPU cluster bring-up, InfiniBand/RoCE fabric validation, HPC benchmarking and remediation, operational models for BMaaS, and cross-team product feedback. Act as primary technical customer contact, run proofs-of-concept, collaborate with engineering teams, and support security-sensitive, production-ready supercomputers.

Design, build, and operate a scalable multi-tenant control plane for high-performance AI storage. Optimize exabyte-scale S3-compatible object storage and distributed filesystems using RDMA, SPDK, GPU Direct Storage, and cloud-native tooling. Improve reliability, observability, and performance across storage stacks, collaborate cross-functionally, and mentor engineers.

Design and implement distributed storage solutions for AI workloads, optimize performance, and collaborate with teams to enhance storage capabilities.