Top Tech Jobs & Startup Jobs in Seattle, WA

Design, build, and operate reliable, scalable services across the C+E stack. Automate operations with scripts and CI/CD, use telemetry to detect trends, perform root cause analysis, support dedicated cloud environments, and collaborate across teams to ensure security, compliance, and operational excellence.

Serve as a strategic HR advisor to Microsoft AI leaders, guiding organizational growth, change, workforce planning, talent strategy, leadership effectiveness, and employee experience. Assess organizational health, design workforce structures and operating models, identify talent risks, and collaborate with Recruiting, HR Business Partners, and Centers of Excellence. Lead a team, coach senior leaders, and deliver people solutions supporting business agility and scale.

Analyze AI training and inference workloads, build performance models and tools, evaluate hardware-software trade-offs, run silicon microbenchmarks, and guide architecture decisions for large-scale cloud AI systems. The role requires correlating models with measurements, diagnosing performance gaps, and communicating recommendations through technical reports and visualizations.

Leads and develops an applied science team building AI-powered Excel experiences. Sets scientific and technical direction across machine learning, LLMs, retrieval, agentic systems, evaluation, and production deployment. Translates customer needs and system failure modes into research and product priorities, drives experimentation and releases, establishes quality and safety standards, manages datasets and evaluation frameworks, and partners with engineering, product, customers, and Microsoft AI communities.

Leads a software engineering team developing Azure deployment automation and infrastructure tooling for Microsoft Defender. Responsibilities include hiring and coaching engineers, setting technical direction, overseeing architecture and code reviews, improving CI/CD and deployment safety, troubleshooting production issues, strengthening observability and recovery, and coordinating cross-team delivery. The role emphasizes cloud reliability, security, operational efficiency, and scalable deployment solutions across constrained and regulated environments.

Own complex PCB layouts from engineering requirements through release, including placement, routing, power distribution, stack-ups, impedance control, and HDI design. Collaborate with electrical, mechanical, manufacturing, and verification teams, as well as suppliers, to deliver manufacturable boards and release packages. Conduct design reviews, resolve DRC and mechanical issues, improve ECAD libraries and workflows, and support fabrication, assembly, board bring-up, verification, and corrective revisions.

Manage treasury accounting and financial reporting for investments, derivatives, debt, and other capital markets activities. Execute close processes, reconciliations, variance analysis, and US GAAP reporting while partnering with Treasury, Tax, Legal, CFP&A, engineering, and external providers. Support SAP S/4HANA migration, system testing, data validation, and reporting dependencies. Drive process improvements and apply automation, AI-enabled tools, and data analysis to improve efficiency, scalability, and reporting quality.

Works directly with enterprise customers to diagnose and resolve Windows deployment, management, update, application, performance, reliability, and security challenges. Develops scripts, automation, diagnostic tools, prototypes, configuration changes, and technical solutions; validates improvements using telemetry and evidence. Documents findings, supports product improvements, creates reusable technical guidance, and builds trusted relationships with customers and Microsoft field teams.

Lead design and build of production-ready cloud and AI systems, prioritize security and reliability, ship solutions quickly using modern engineering practices, collaborate with cross-functional teams, mentor engineers, drive customer adoption, and deliver reusable assets and end-to-end complex deliveries.

Lead end-to-end data science for customer-embedded, production solutions: acquire and prepare messy datasets, develop and evaluate models tied to business outcomes, run experiments, deploy operational models at scale, coach cross-disciplinary teams, and drive strategy, ethics, and privacy discussions.