Top Infrastructure Engineer Jobs in San Francisco, CA

Leads infrastructure engineering initiatives focused on wireless and WAN networking, including architecture, implementation, modernization, incident leadership, automation, and cloud migration. Advises on complex infrastructure issues, coordinates stakeholders and vendors, ensures compliance, security, resiliency, and auditability, and mentors engineers. Uses validated enterprise AI capabilities to analyze infrastructure signals, recommend mitigations, and improve operational processes.

Designs, deploys, and supports enterprise infrastructure across data centers, offices, engineering environments, and hybrid cloud platforms. Responsibilities include Active Directory, compute, virtualization, storage, Windows and Linux systems, backup and disaster recovery, monitoring, automation, Kubernetes support, and infrastructure resiliency. The role leads complex technical initiatives, troubleshoots critical incidents, develops infrastructure standards, partners with cybersecurity and networking teams, and mentors engineers. Regular on-site presence in the San Mateo Bay Area and occasional travel are required.

Lead design, operation, and continuous improvement of enterprise DNS and IPv6 capabilities. Architect DNS and IPv6 addressing, implement reverse DNS delegation, execute transition strategies (Dual-Stack, NAT64, DNS64), troubleshoot resolution and routing issues (dig, nslookup, BGP, OSPFv3), automate operational tasks, document runbooks, and apply enterprise-authorized AI with validation and auditability in controlled change environments.

Lead customer-embedded infrastructure delivery from hardware validation and capacity onboarding through production operations. Build automation for provisioning, fleet management, observability, and reliability; coordinate Cloudflare infrastructure, hardware, data center, supply chain, network, and customer engineering teams. Own technical relationships, capacity planning, incident response, operational readiness, and feedback to product teams. The role requires regular on-site customer engagement in Austin or San Francisco.

Leads the design, deployment, monitoring, and troubleshooting of cooling infrastructure for high-density data centers. Serves as the primary cooling subject matter expert and secondary power expert, establishes facility standards, selects scalable liquid-cooling systems, develops thermal monitoring and alerting capabilities, and partners with colocation, hardware, infrastructure, and operations teams. Manages, hires, mentors, and develops an engineering team while improving reliability and facility readiness for next-generation data center technologies.

Build and operate cloud, HPC, CI/CD, regression, data, and observability infrastructure supporting custom silicon development. Develop developer tools, APIs, automation, scheduling systems, and reliable workflows for hardware engineering teams. Scale cloud environments and compute clusters, improve platform reliability, troubleshoot distributed systems, and optimize performance, capacity, cost, and operational efficiency across silicon design and verification workflows.

Build and operate reliable, scalable cloud infrastructure for AI workflows, advertising operations, and data systems. Responsibilities include designing asynchronous and event-driven systems, maintaining CI/CD and infrastructure automation, improving observability, security, performance, and cost efficiency, and leading incident response and disaster recovery. The role partners across engineering and product teams on capacity planning, reliability, troubleshooting, and post-incident improvements.

Build and maintain CrowdStrike’s golden-image platform and automated pipelines across Linux, macOS, and Windows. Develop Python automation for image builds, validation, drift detection, and testing; manage infrastructure as code with Ansible, Packer, and Terraform; integrate Jenkins, GitLab CI, and Artifactory; and support image lifecycle operations. The role includes troubleshooting production issues, security hardening, compliance collaboration, documentation, cross-team partnership, and participation in on-call rotations.

Leads enterprise-scale Microsoft Hyper-V infrastructure engineering across global data centers. Designs resilient clusters, automates provisioning and compliance with PowerShell and DSC, develops C#/.NET orchestration services, benchmarks performance, troubleshoots full-stack infrastructure issues, evaluates server hardware, remediates vulnerabilities, documents architectures, and mentors engineers. The role also promotes validated, auditable use of enterprise AI capabilities in infrastructure operations.

Develop and maintain test infrastructure for autonomous vehicle manufacturing, including test frameworks, server infrastructure, applications, dashboards, databases, APIs, containerization, CI/CD pipelines, and tester orchestration. The role supports factory testing across manufacturing sites and collaborates with hardware, software, and manufacturing teams. Responsibilities include monitoring infrastructure health, managing cloud and on-premise deployments, and building tools and common libraries for test engineers.

Owns cloud infrastructure and deployment pipelines as the sole infrastructure engineer for a small product team. Responsibilities include CI/CD, AWS architecture, security controls, infrastructure as code, monitoring, incident readiness, networking, cost optimization, vulnerability management, and customer security reviews. The role requires independently building and operating reliable production systems across development, staging, and production environments.

Manage the lifecycle, security, reliability, and cost optimization of large-scale AWS infrastructure. Responsibilities include patching and upgrades, vulnerability remediation, automation with scripting and infrastructure tools, incident response, troubleshooting, monitoring, and compliance. The role requires extensive AWS experience across multi-account environments, Kubernetes and Terraform expertise, operational scripting, cloud security hardening, and monitoring with tools such as Datadog or CloudWatch.

Owns deployment of quantum computing systems across customer sites, research institutions, partner locations, and cloud platforms. Responsibilities include site assessment, installation, commissioning, infrastructure development, deployment validation, customer coordination, incident response, observability, root-cause analysis, CI/CD, test environments, documentation, and reliability improvements. The role requires hands-on DevOps, cloud, networking, Linux, Kubernetes, infrastructure-as-code, and production support experience, with international travel for installations and onboarding.

Build and operate Benchling’s AWS cloud infrastructure, including Kubernetes, networking, secrets, observability, infrastructure-as-code, and cost governance. Develop internal APIs, automation, CLIs, serverless tools, and AI assistants. Own complex projects from design through production, establish technical standards, support incident response and on-call operations, and collaborate across engineering teams to improve secure, reliable, and cost-effective platform delivery.

Design, deploy, activate, and operate global WAN infrastructure across data centers, network PoPs, carriers, and cloud providers. Troubleshoot physical, optical, Layer 2, and Layer 3 connectivity issues; provision circuits; monitor network health; and build automation for network operations. The role also involves physical network design, cross-team coordination, service restoration, network expansion, and participation in an on-call rotation.

Design, operate, and scale Azure cloud infrastructure and backend platform services supporting real-time radar sensor data. Build infrastructure as code, containerized workloads, Python services, distributed data systems, and CI/CD pipelines. Own platform architecture, networking, security, reliability, observability, incident response, and secure identity and secrets management. Collaborate across engineering teams to evolve a production platform for growing sensor fleets, customers, and deployments.

Leads infrastructure engineering projects involving network architecture, migration, performance testing, troubleshooting, automation, resiliency, and cloud operations. Designs and implements infrastructure changes across platforms, performs pre- and post-migration validation and cutovers, and applies Cisco, Arista, Fortinet, BGP, OSPF, switching, scripting, and AI-assisted workflows. Ensures recommendations and changes meet security, sensitivity, auditability, and resiliency standards while collaborating cross-functionally.

Lead design, build, and delivery of a next-generation SD‑WAN ecosystem. Produce HLD/LLD artifacts, define requirements, lead testing and automation, apply security and resiliency controls, maintain audit-ready documentation, and coordinate stakeholders to mitigate operational and technology risks while leveraging enterprise AI-assisted practices.

Administer and optimize SOLIDWORKS and PDM infrastructure for mechanical engineering teams. Build CAD automation and CI workflows, integrate PDM with design-control and manufacturing systems, automate BOMs and build routes, secure on-premise equipment, support 3D printing and machine-shop tooling, and establish company-wide CAD and tooling standards.

Run and scale highly available Kubernetes clusters across AWS, GCP, and GPU providers. Own production model-serving infrastructure, troubleshoot GPU systems, extend deployment tooling, and build observability for latency-sensitive services. Design automated failover, self-healing, alerting, and traffic-routing systems while partnering with optimization engineers to ensure performance under live traffic. The role requires extensive infrastructure experience, staff-level individual contributor capability, production Kubernetes expertise, GPU and CUDA troubleshooting, LLM serving knowledge, and high-performance networking experience.

Lead the architecture, development, and operation of cloud infrastructure for an AI-native legal platform. Own CI/CD, developer tooling, Kubernetes and containerized workloads, AI infrastructure, observability, security, compliance, reliability, scalability, and cost optimization. Partner with engineering and product teams, establish infrastructure standards, and hire and mentor future infrastructure engineers while ensuring sensitive legal data is handled securely.

Own the design and implementation of Azure platform infrastructure for secure, repeatable enterprise AI deployments. Build IaC modules, identity and security controls, networking, CI/CD automation, observability, reliability tooling, and customer environment automation. Partner with product engineers and enterprise teams to standardize deployments across complex Azure environments, including decisions involving containers, scaling, resilience, isolation, and cost.

Maintains secure, reliable, and highly available servers, networks, operating systems, middleware, and multi-cloud infrastructure. Responsibilities include installation, upgrades, monitoring, troubleshooting, automation, security patching, disaster recovery, job scheduling, vendor coordination, documentation, and 24x7 on-call support. The role also supports development, test, and production environments, leads infrastructure projects, mentors technical staff, and recommends improvements to infrastructure performance, security, and lifecycle management.

Implements and supports enterprise AI infrastructure platforms across client environments. Configures Kubernetes, workload schedulers, GPU resource governance, containers, observability, security, and related platform services. Performs discovery, deployment, integration, upgrades, troubleshooting, validation, documentation, and knowledge transfer. Collaborates with cross-functional technical teams, contributes to implementation plans and Statements of Work, manages project deliverables, and provides client-facing consulting support. Travel and occasional extended or weekend work may be required.

Build and operate production GPU compute infrastructure across owned hardware, neocloud providers, bare metal, VMs, and containers. Own fleet strategy, provisioning, recovery, host hardening, workload isolation, provider integrations, hardware deployment, and cross-layer failure debugging. Translate heterogeneous GPU capacity into reliable, secure, operable infrastructure while balancing architecture, implementation, and production operations.