Top Tech Jobs & Startup Jobs in Seattle, WA

Leads technical sales engagements for Microsoft AI Business Process solutions, using demos, proofs of concept, hackathons, and architecture workshops. Partners with enterprise developers, platform leaders, and engineering teams to design secure, scalable solutions across Dynamics 365, Power Platform, and cloud environments. Resolves technical objections, supports production deployments, develops expertise in business applications, and represents Microsoft through customer forums and developer communities.

Lead end-to-end delivery of strategic data science and AI solutions for AI infrastructure. Work with telemetry and experimentation at fleet scale to build, deploy, and measure predictive and prescriptive models. Partner with stakeholders, present insights, enable adoption, and promote responsible AI. Collaborate closely with data engineers and infrastructure teams to productionize scalable ML solutions.

Design and optimize networking infrastructure for Azure AI supercomputing clusters. Develop RDMA communication libraries, transport protocols, distributed systems, observability tools, and performance optimizations. Analyze latency, throughput, congestion, scalability, and fault tolerance across large GPU and accelerator environments. Lead technical architecture, write design specifications, resolve complex production networking challenges, and collaborate with hardware, silicon, AI framework, and infrastructure teams.

Lead security reviews, code audits, penetration testing, vulnerability research, and mitigation efforts for Microsoft Windows services. Develop reusable security tools and agents, identify attack vectors and architectural risks, demonstrate exploit impact, and collaborate with product engineering teams to design scalable defenses and improve security investments.

Secure Microsoft Windows online services through offensive security, code and deployment reviews, penetration testing, vulnerability research, and scalable mitigation development. Build reusable security review tools and agents, demonstrate exploit impact, identify novel attack vectors, bypass security controls, and collaborate with product engineering teams to strengthen architecture and defenses.

Own and improve sales quota-setting models and methodologies using statistical modeling, forecasting, optimization, machine learning, and AI. Validate data, assumptions, model outputs, and business impact while partnering with Finance, Sales Compensation, Analytics, Engineering, and business stakeholders. Develop scalable analytical workflows and LLM solutions, including RAG applications, and communicate quantitative findings clearly to influence sales strategy, incentive programs, and operational decisions.

Leads cybersecurity competitive strategy and execution, including deal coaching, competitive positioning, win/loss analysis, compete playbooks, field enablement, and cross-functional recommendations for sales, product, engineering, marketing, and partner teams. The role focuses on Google Security, Mandiant, Wiz, and Microsoft Security competitive scenarios, translating market and customer insights into scalable go-to-market motions and product strategy.

Business Architect role within Microsoft’s Sales Strategy Enablement organization. The provided description primarily includes compensation information, equal employment opportunity details, and application timing; specific responsibilities and qualifications are not listed.

Leads customer success strategy for complex Defense Industrial Base accounts. Builds executive relationships, develops success plans, orchestrates Microsoft resources, drives Azure and Microsoft solution adoption, accelerates consumption, manages escalations, mitigates delivery risks, and improves customer health and retention. Partners with sales, engineering, support, and delivery teams while influencing stakeholders without direct authority.

Own product strategy and multi-year roadmaps for GPU back-end networking. Translate AI workload needs into requirements, lead products through qualification and deployment, coordinate engineering and business teams, influence suppliers, and improve performance, reliability, cost, observability, and launch readiness.