Top Engineering Jobs in Seattle, WA

Leads architectural, MEP, and LV/IT design for multiple data center projects from feasibility through construction support. Coordinates consultants, providers, contractors, internal engineering SMEs, and vendors; manages design standards, deviations, budgets, schedules, equipment submittals, reviews, reporting, and site visits. Ensures high-density data center designs meet performance, efficiency, scalability, quality, and compliance requirements. Requires 25% travel to data center sites.

Leads technical due diligence for prospective data center sites, evaluating electrical, mechanical, civil, structural, architectural, utility, zoning, and infrastructure feasibility. Reviews provider proposals, capacity data, conceptual layouts, and building documentation; identifies risks, upgrades, cost and schedule impacts; prepares go/no-go recommendations and technical assessments. Coordinates with utilities, landlords, developers, internal subject matter experts, and design teams, then hands secured sites to Design Managers. Frequent travel is required.

Design and review data center white space infrastructure for high-density computing environments. Coordinate electrical, mechanical, cooling, low-voltage, cabling, and network pathway systems; review drawings, submittals, RFIs, and field conditions; oversee consultants; resolve design and constructability issues; and support construction, commissioning, and deployment. Contribute to design standards, scalability, technical documentation, and mentorship across CoreWeave’s data center portfolio.

Serves as a technical lead for customers using CoreWeave cloud infrastructure, with emphasis on Kubernetes in high-performance computing environments. Responsibilities include designing and deploying tailored solutions, leading proofs of concept, optimizing AI/ML workloads, conducting technical reviews, advising on product strategy, collaborating with engineering teams, and representing CoreWeave at industry events.

Leads systems engineering teams developing high-throughput file, block, and object storage for AI cloud infrastructure. Drives architecture, performance tuning, latency optimization, benchmarking, and 10x scaling across distributed storage systems. Provides technical mentorship, performance management, recruitment, and cross-functional leadership while maintaining a coding-focused culture and maximizing GPU utilization.

Lead and develop an infrastructure engineering team responsible for internal Kubernetes platforms and foundational services. Set roadmaps, ownership, operating practices, and success metrics; guide reliable infrastructure and automation; establish testing, observability, SLO, incident response, change management, and on-call practices; resolve cross-team dependencies; and manage hiring, coaching, performance, priorities, and risk communication.

Design, build, and operate secure, high-performance sandboxed runtime environments for multi-tenant Kubernetes workloads. Develop GPU-aware scheduling, isolation, and resource management strategies; integrate container runtimes, lightweight virtual machines, and virtualization technologies; optimize container, VM, I/O, and GPU performance; conduct profiling and benchmarking; and contribute to Linux, runtime, virtualization, GPU, and security architecture.

Build and operate CoreWeave’s multi-cloud internal infrastructure across GCP, Azure, and AWS. Manage cloud foundations, IAM, networking, Terraform infrastructure as code, monitoring, logging, CI/CD, backups, disaster recovery, and production reliability. Troubleshoot complex infrastructure and application issues, support cloud migrations and acquisitions, implement secure architecture patterns, and contribute to incident response and root-cause analysis. Mentor junior engineers and communicate technical decisions across teams.

Design, build, and operate secure sandboxed runtime environments for Kubernetes and GPU-accelerated workloads. Develop GPU-aware scheduling, isolation, and resource management strategies; optimize container, VM, I/O, and GPU performance; conduct profiling and benchmarking; and contribute to Linux, container runtime, virtualization, and GPU driver architecture. Collaborate with security, platform, and infrastructure teams to establish runtime isolation and performance standards for multi-tenant systems.

Own and evolve a Kubernetes-native test framework that qualifies host images on real hardware. Build test harnesses, extend coverage into HPC, Slurm-on-Kubernetes and firmware/hardware, keep CI fast and reliable at fleet scale, and own results, reporting, and triage. Collaborate with kernel, firmware, imaging, and HPC teams and explore LLM-driven log triage and failure classification.