Top Tech Jobs & Startup Jobs in Seattle, WA

Lead end-to-end power architecture for high-power AI accelerator SoCs across silicon, package, board, and system levels. Define power-management, power-delivery, thermal, and workload-aware architectures; establish power budgets and system interfaces; evaluate performance, reliability, cost, and implementation tradeoffs; and provide technical leadership through design, silicon bring-up, characterization, and deployment.

Lead applied science for Microsoft 365 Copilot by developing reliable long-horizon agentic capabilities, frontier-model evaluation methods, offline benchmarks, online experimentation, ML pipelines, and performance metrics. Own experiments and ML projects from inception through production, build workflow tools, shape technical roadmaps, communicate findings to leadership, mentor scientists and engineers, and help grow the applied science recruiting and research culture.

Manage operating expense P&L outcomes, develop resource blueprints, guide hiring and allocation decisions, analyze headcount, cost-per-head, and program spending, and partner with finance and business leaders on budgeting, forecasting, financial targets, and operational efficiency.

Leads cross-functional technical programs for Azure cloud hardware, from concept through launch and deployment. Coordinates hardware and software engineering, sourcing, supply chain, networking, and data center operations teams. Establishes program plans, milestones, technical requirements, risk mitigation, stakeholder alignment, and executive communications. Drives new product introduction, supplier collaboration, process improvement, and delivery of scalable server platform solutions on schedule and within budget.

Design, build, and operate large-scale, highly available Responsible AI cloud services. Lead projects, ensure production readiness and DevOps practices, integrate with Azure AI products, and collaborate with engineers, scientists, and stakeholders to deliver scalable, observable, and secure Responsible AI features and infrastructure.

Leads cross-functional technical programs that transform large datasets into actionable insights. Designs analytics, automation, AI, and low-code/no-code solutions; collaborates with engineering and business stakeholders; prioritizes projects; establishes data standards; and delivers stable, compliant, scalable platforms and visualizations using Microsoft technologies.

Build and deploy AI-powered agents, automations, applications, and workflow solutions for Microsoft business teams. Translate ambiguous needs into prototypes and production systems using Power Platform, Microsoft 365, GitHub, Azure AI, APIs, and full-stack technologies. Lead stakeholder discovery, process redesign, testing, deployment, adoption, lifecycle management, responsible AI practices, and outcome measurement while collaborating across global technical and business teams.

Develop Windows Compatibility tools, automation frameworks, infrastructure, and AI-powered solutions to identify regressions, validate applications, investigate compatibility issues, and improve Windows experiences. The role involves scalable software design, test automation, root cause analysis, collaboration with Microsoft teams and partners, and modernizing engineering tools across Windows, operating systems, and cloud platforms.

Lead architecture and technical direction for scalable AI agent security infrastructure. Design and build distributed services and full-stack experiences for agent security, policy, and tool governance. Establish experimentation frameworks, evaluation methodologies, data quality standards, and success criteria. Drive cross-team architectural alignment, improve scalability and reliability, mentor engineers, and deliver secure LLM-powered applications and agent workflows.

Design, build, and operate globally scalable backend services and APIs powering Outlook and Microsoft 365. Own features end to end, including architecture, implementation, testing, deployment, monitoring, incident response, and continuous improvement. Solve distributed-systems challenges involving reliability, performance, scalability, security, and fault tolerance. Collaborate across teams on API contracts and customer experiences while improving engineering productivity, modernizing services, and contributing to an inclusive engineering culture.