Top Tech Jobs & Startup Jobs in Seattle, WA

Lead as a customer‑embedded principal engineer to design, build, and ship production-grade solutions. Translate business needs into technical approaches, influence senior stakeholders, accelerate delivery in ambiguous environments, and transition work to FDE crews while driving long-term account impact.

Design and build petabyte-scale multimodal data pipelines and infrastructure (text, audio, images, video). Own and maintain systems like Spark, Ray, and vector databases, partner with pre/post-training teams to improve data recipes through experimentation, and support large-scale dataset storage and processing for AI model training.

Lead large-scale, cross-functional data center delivery programs by applying technical knowledge in mechanical, electrical, networking, and building automation systems. Drive pilots and transformation initiatives, implement templates and automation, design reporting for actionable insights, manage scope/schedule/budget/quality, and influence executive stakeholders to deliver on-time, on-budget data center projects.

Lead consultative, value-driven enterprise sales to plan, orchestrate, and deliver AI Workforce solutions (Copilot, Windows 365, Viva, Agents). Build stakeholder strategies, drive pipeline, cross-sell/up-sell, and partner with internal teams to scale AI adoption and measurable business outcomes.

Lead technical ownership of InfiniBand and GPU interconnect fabric operations for hyperscale AI supercomputers. Drive incident response, deep multi-layer debugging across hardware/firmware/drivers/OS, and define failure models, playbooks, telemetry, and automation to improve reliability, observability, and scalability of GPU clusters and platform SLAs.

Manage and coach a team of datacenter trainers to design and deliver technical workforce training, assess learning needs, close operational training gaps, partner with site managers, and align training with availability, safety, and throughput goals across global datacenters.

Design, curate, and evaluate high-quality multimodal datasets for foundation models. Build scalable ingestion, preprocessing, filtering, annotation pipelines; run data ablations and analyses; create auditing, visualization, and versioning tools; collaborate with Safety, Ethics, and research teams to ensure data quality, privacy, and responsible AI alignment.

Design and develop multimodal foundation-model algorithms and architectures, run large-scale experiments, improve training and deployment efficiency, build datasets and pipelines, perform rigorous evaluation and ablation studies, and collaborate with infrastructure, data, and product teams to responsibly advance AI systems.

Drive product strategy and KPIs for backend networking of ultra-large AI supercomputers. Identify failure points, lead remediations and roadmap changes, and coordinate cross-functional teams including customers, datacenter operators, vendors, and product groups to maximize uptime and AI workload throughput.

Design, implement, and optimize low-level software for Azure HPC/AI VMs. Diagnose HW/SW integration and performance issues, drive cross-team solutions, maintain service stability, and develop operational playbooks.