Top Engineering Jobs in San Francisco, CA

Build and maintain developer workflows, CI/CD and deployment automation, containerized development environments, SDK packaging and release pipelines, AI performance dashboards, and productivity tools for AI frameworks. Design scalable software and developer tools for novel hardware platforms, collaborate with hardware and ML teams, manage C++ codebases, establish engineering standards, and improve software performance and production readiness.

Lead performance analysis and optimization for large-scale HPC and AI workloads across InfiniBand-connected GPU clusters. Diagnose network bottlenecks, tune RDMA and QoS, analyze fabric telemetry, optimize collective communication, develop performance tooling, and benchmark distributed workloads. The role also collaborates with operations and hardware vendors on interconnects, firmware, topology, and scalable communication performance.

Lead architecture and hands-on development for Microsoft’s virtualization platform, focusing on hypervisor and VMM capabilities. Design and implement systems software across Windows, Linux, and macOS; improve performance, security, reliability, and cost efficiency; enable virtualization on new silicon; diagnose low-level hardware and software interactions; mentor engineers; and influence technical strategy across Windows Core and Azure.

Lead architecture and technical strategy for Azure cloud-scale distributed data platforms processing network telemetry. Design streaming and batch systems focused on scalability, reliability, performance, data quality, security, and operational efficiency. Drive cross-team architectural decisions, platform capabilities, production readiness, and continuous improvement. Serve as a technical authority, mentor engineers and leaders, and influence engineering standards across Azure Networking.

Design and verification engineer responsible for validating complex IP, subsystems, and full-chip hardware for Azure cloud servers. Duties include developing test cases and plans, evaluating verification tools, creating performance simulators and prototypes, reviewing chip architecture, managing implementation schedules and risks, coordinating suppliers and training, and documenting hardware specifications. The role requires expertise in hardware verification workflows and collaboration across engineering teams.

Leads software engineering for Windows Core OS, defining requirements and architecture, developing maintainable code, mentoring engineers, coordinating cross-product plans, supporting on-call operations, and improving product reliability, observability, availability, efficiency, and performance.

Leads architecture, hands-on software engineering, and production deployment for strategic customer projects. Drives AI innovation, platform resiliency, security, observability, reliability, and performance improvements. Partners with executives, engineering, product, and customer teams to identify and execute high-value programs, remove production blockers, measure customer outcomes, and share technical best practices across the organization.

Provides technical leadership for Azure SQL databases supporting a large-scale Azure service. Owns database reliability, performance, availability, capacity planning, schema changes, migrations, observability, incident response, and automation. Partners with software engineers, architects, and SREs to improve scalability, operational excellence, and long-term reliability. Leads root-cause analysis, reduces technical debt, establishes database standards, and influences technical direction across teams.

Designs, builds, and operates distributed storage and file-system platforms for large-scale AI training and inference on Azure. Responsibilities include optimizing Kubernetes and GPU workloads, developing caching architectures, improving reliability and observability, troubleshooting cross-layer production issues, and supporting geo-distributed storage and disaster recovery. The role leads architecture reviews, shapes storage strategy, mentors engineers, and collaborates across infrastructure, networking, operating systems, and AI platform teams.

Design and scale ultra-low-latency Ethernet and InfiniBand fabrics for hyperscale AI training. Engineer ROCE transport, congestion control (ECN/WRED/DCTCP), telemetry, routing, and observability; bring up clusters, benchmark AI workloads, debug performance, and collaborate with silicon and datacenter partners to deploy large-scale AI infrastructure.