Top Engineering Jobs in San Francisco, CA

Build and operate autonomous cloud operations capabilities for Microsoft's Kubernetes fleets. Design distributed platform and orchestration services enabling AI agents to execute deployment, resiliency, recovery, and optimization workflows. Implement safety controls, observability, evaluations, and rollback mechanisms. Own features from design through production, investigate incidents, improve reliability, make architectural decisions, and mentor engineers.

Lead the design, development, deployment, and operation of Azure regional networking infrastructure spanning router hardware, SONiC, optical systems, and distributed orchestration. Develop maintainable code, improve reliability and observability, apply AI-driven engineering, coordinate cross-functional projects, and provide technical leadership across engineering, hardware, supply chain, datacenter operations, research, and external partners.

Designs, implements, and operates networking architectures for Azure Dedicated environments, including hybrid connectivity, ExpressRoute, and SDN solutions. Integrates third-party platforms, optimizes performance and reliability, troubleshoots complex hybrid or multi-cloud issues, and supports automation, observability, live-site operations, workload migration, and disaster recovery. Collaborates with Azure teams and external partners to establish standards and improve services.

Design and build high-performance networking infrastructure for distributed AI training and inference in Azure. Architect low-latency, low-jitter communication frameworks, optimize systems for scalability and reliability, debug complex networking issues, and support petabyte-scale data transfer. Lead technical design, mentor engineers, improve observability and operational reliability, and participate in on-call support for large-scale AI infrastructure.

Architect and deliver a fleet-scale observability platform for AI supercomputers. Lead telemetry ingestion, processing, storage, querying, topology modeling, and health visualization across GPUs, hosts, networks, storage, and facilities. Establish signal standards, integrate first-party and third-party capacity data, and enable AI-assisted anomaly detection and root-cause analysis. Partner across engineering, operations, customers, and datacenter technicians to create secure workflows, validate repairs, improve reliability, and reduce diagnosis and recovery times.

Designs and leads secure, scalable Azure cloud and hybrid infrastructure solutions for nonprofit customers. Responsibilities include platform modernization, sovereign cloud engagements, workload migration, networking architecture, technical workshops, live demonstrations, prototyping, proofs of concept, and customer advisory. The role requires expertise in Windows, Linux, Oracle, enterprise applications, Azure services, Kubernetes, security, compliance, resiliency, and AI-enabled infrastructure transformation.

Design, develop, deploy, and operate large-scale Azure software load-balancing and distributed networking systems. Improve scalability, performance, reliability, security, telemetry, alerting, automation, and self-healing capabilities. Diagnose network and system bottlenecks, participate in on-call operations, restore service health, estimate and break down work, develop features iteratively, and mentor engineers on coding and design practices.

Provides technical leadership for AI framework, performance engineering, benchmarking, and developer productivity initiatives. Owns architecture, technical vision, roadmaps, and multi-release execution while guiding cross-team investigations across models, compilers, runtimes, systems, services, and hardware. Leads architectural decisions, mentors engineers, contributes to implementation and debugging, and develops scalable measurement and observability capabilities. The role focuses on improving AI model onboarding, runtime performance, reliability, hardware utilization, and Azure capacity efficiency.

Develop and operate cloud-native container orchestration and AI infrastructure for Azure Kubernetes Service. Responsibilities include advancing Kubernetes capabilities, improving service reliability and engineering velocity, automating incident prevention and remediation, integrating AI tools, and building observability systems. The role focuses on distributed systems, containers, Kubernetes, Linux, site reliability engineering, and scalable AI workloads across cloud and edge environments.

Lead architecture, development, and operational excellence for Azure Boost DPU software at hyperscale. Build low-level systems spanning operating systems, virtualization, networking, storage, device management, and hardware interfaces. Drive performance, reliability, security, and scalability improvements while collaborating with hardware, firmware, silicon, and platform teams. Lead cross-functional technical execution, design reviews, engineering best practices, and mentorship across multiple teams.