Top Tech Jobs & Startup Jobs in San Francisco, CA

Leads Microsoft’s Global Business Operations team and enterprise commercial operating rhythms. Sets strategic direction, governance, performance standards, and execution frameworks; drives executive alignment, stakeholder influence, operational excellence, AI-enabled process improvement, and cross-functional follow-through. Builds and develops a high-performing team, oversees complex program portfolios, synthesizes business insights, manages risks and dependencies, and ensures executive decisions translate into measurable outcomes across global sales and commercial organizations.

Manages medium-enterprise customer accounts, builds executive relationships, generates pipeline, forecasts revenue, and drives cloud and AI solution adoption. The role coordinates internal specialists and partners, manages territories and sales pipelines, supports upsell, co-sell, and renewals, and advocates for customer needs. It also requires maintaining product, industry, and competitive expertise while orchestrating resources to deliver digital transformation outcomes.

Own operations and reliability for hyperscale Azure GPU clusters and interconnect fabrics. Lead incident triage, mitigation, recovery, root-cause analysis, and cross-stack debugging across hardware, firmware, drivers, PCIe, GPUs, and software. Develop automation, telemetry, diagnostics, playbooks, and escalation frameworks to improve observability, issue detection, and mitigation times while supporting large-scale AI and HPC workloads.

Leads the Americas lease commissioning program for Microsoft datacenter capacity. Manages commissioning strategy, governance, standards, readiness reviews, Integrated Systems Testing, operational turnover, and Ready for Service milestones. Directs Lease Commissioning Managers, oversees lease providers, manages portfolio risks and performance, and coordinates engineering, operations, networking, finance, and delivery teams. Ensures facilities are safely commissioned, validated, operationally ready, and aligned with Microsoft standards, contractual obligations, schedules, and capacity objectives.

Lead architecture and technical direction for Azure cloud infrastructure, Kubernetes platforms, storage systems, and machine learning infrastructure. Design scalable distributed systems for model training, inference, data processing, and platform services. Improve reliability, security, resource efficiency, and operational performance while supporting MLOps and production AI workloads. Partner with engineering and product leaders, establish technical standards, guide cross-team architecture decisions, and mentor engineers.

Provides technical leadership for global datacenter battery monitoring system deployments. Responsibilities include troubleshooting complex issues, establishing global standards, managing lab deployments, testing system configurations, resolving security findings with suppliers, and improving system reliability, availability, and infrastructure interactions. The role also supports automation, cloud or distributed systems, budgeting, purchasing, and project management activities.

Designs secure, scalable AI and cloud architectures for Microsoft partners. Leads architecture sessions, develops proofs of concept and pilots, provides technical implementation guidance, supports legacy-to-cloud transitions, and helps partners build production-ready Copilot, agentic, and managed-service solutions. Serves as a technical bridge between Microsoft engineering and strategic partners while advising on data, applications, APIs, security, governance, and enterprise AI adoption.

Designs and operates offensive cyber-capability evaluations for frontier AI models and agentic systems. Builds cyber ranges, vulnerable applications, exploit-development targets, evaluation harnesses, telemetry, scoring, and containment controls. Executes controlled experiments, analyzes model behavior and evaluation artifacts, documents findings, and collaborates with red-team operators, researchers, engineers, and Responsible AI stakeholders.

Design, implement, and optimize core components of a hyperscale distributed file system and metadata service on Azure. Work on DPU-based storage servers, ensure high availability, reliability, durability, and cost efficiency. Produce design documents, break down features, estimate work, implement code, act as on-call DRI, and improve observability and operations at scale.

Develops and operates large-scale Azure automation for datacenter processes, including workload migration, server decommissioning, orchestration, validation, monitoring, and reliability improvements. Designs, implements, optimizes, debugs, and maintains software while collaborating with infrastructure and partner teams. Acts as an on-call responsible individual, resolves service issues, improves observability and efficiency, and guides other engineers.