Top Infrastructure Engineer Jobs in San Francisco, CA

Build, secure, scale, and maintain cloud infrastructure supporting SaaS products, databases, storage, search, microservices, and machine-learning pipelines. Operate Kubernetes workloads, automate infrastructure with Terraform and Helm, improve reliability and observability, optimize costs, define SLOs and SLAs, participate in incident response and on-call rotations, address vulnerabilities, support customer security integrations, and maintain compliance with SOC 2, HIPAA, and GDPR requirements.

Own infrastructure and platform engineering end to end as the first dedicated infrastructure hire. Design, build, scale, and operate runtime, deployment, recovery, monitoring, and observability systems; support automated production code workflows; and deliver a dedicated-instance platform for customer-managed cloud accounts. Establish technical standards, contribute to hiring, and eventually lead the infrastructure team.

Own end-to-end deployment of a software platform into customer-managed private cloud and on-premises environments. Partner with customer engineering and security teams, troubleshoot Kubernetes, cloud IAM, and networking issues, and build monitoring, telemetry, and automation for repeatable deployments. The role also involves understanding hardware supporting machine-learning workloads and occasional customer site visits.

Build and operate AWS cloud infrastructure using Terraform/OpenTofu and Spacelift. Lead multi-account architecture migrations, develop reusable infrastructure modules, improve reliability and disaster recovery, support compliance, troubleshoot cloud environments, and automate recurring issues. Partner with engineering teams, strengthen observability and incident response, and participate in an internal infrastructure support on-call rotation. The role also drives multi-quarter platform initiatives with significant autonomy.

Architect and build backend infrastructure for an AI-driven enterprise email platform. Design scalable distributed systems ingesting millions of messages/day, implement secure, compliance-ready and on-prem-capable systems, and serve as a hands-on senior engineer driving a zero-to-one product build.

Own and operate production infrastructure for large-scale automated web data collection. Design proxy pools, session handling, isolated outbound traffic, browser identity systems, and automated challenge handling. Improve request success rates against anti-bot defenses, manage reliability and costs, investigate intermittent failures, and provide full production ownership including on-call responsibilities.

Design, deploy, and maintain hardware-in-the-loop testbeds, electrical ground support equipment, and automated testing tools for spacecraft systems. Build Python frameworks for simulation, fault injection, mission scenarios, and continuous integration. Collaborate with software, hardware, systems, and operations teams while troubleshooting issues across embedded hardware, networking, software, and system configuration.

Designs and evolves AWS infrastructure as code using CDK, develops backend software primarily in TypeScript, and applies secure engineering practices for regulated environments. The role contributes to architecture, code reviews, CI/CD pipelines, production support, observability, and on-call operations. It collaborates cross-functionally, builds scalable and reusable systems, supports SOC 2 compliance, and uses AI coding assistants to improve development, testing, and documentation.

Own and improve Kit’s production infrastructure across AWS, Kubernetes, databases, networking, CI/CD, monitoring, and platform tooling. Lead upgrades, incident response, cost optimization, documentation, and self-service paved paths. Participate in a three-person on-call rotation and build reliable infrastructure that supports engineers, non-engineers, and AI agents.

Own and evolve production infrastructure for AI workloads, including Kubernetes, cloud-native migrations, scheduling, orchestration, observability, infrastructure as code, deployment workflows, security, reliability, and incident recovery. Partner with engineering and business operations teams to build dependable platform capabilities. The role requires deep production Kubernetes experience, strong cloud and Linux fundamentals, architectural judgment, automation skills, and end-to-end ownership of infrastructure systems.

Design, operate, and evolve production GCP infrastructure, including GKE clusters, networking, IAM, shared services, and Terraform automation. Troubleshoot complex Kubernetes, Linux, networking, DNS, and distributed-systems issues; improve observability, security, scalability, reliability, and cost efficiency. Lead upgrades, migrations, architecture improvements, technical reviews, and mentorship while partnering with Platform Engineering, SRE, and Security teams.

Design, build, and scale vehicle data-collection networking and infrastructure. Integrate software with onboard compute, sensors, and navigation. Build CI/CD, ensure performance, security, and operational excellence for an autonomous vehicle fleet.

Build and maintain cloud infrastructure, developer platforms, CI/CD pipelines, edge services, and GPU compute capacity. Improve reliability through monitoring, alerting, SLOs, incident response, and automation. Manage containers, authentication systems, source control, and build infrastructure while participating in on-call operations and applying AI-assisted tools to infrastructure engineering.

Deploy and operate cloud-native AI infrastructure across AWS, GCP, and Azure, including Kubernetes, networking, identity, security, multi-region, and data residency configurations. Build infrastructure as code, CI/CD, GitOps, observability, and alerting while supporting research, ML, and GPU platforms. Partner with clients and internal engineering and science teams on enterprise deployments, compliance, reliability, cost, and production hardening.

Designs, deploys, migrates, secures, and operates production Azure infrastructure across hybrid VMware and Windows environments. Responsibilities include Azure networking, platform services, disaster recovery, migrations, Terraform automation, Azure DevOps pipelines, identity and governance, monitoring, cost management, troubleshooting, and compliance. The engineer supports application platforms including AKS, App Services, databases, and integrations while participating in incident response, change management, on-call duties, and occasional after-hours cutovers.

Design and scale Macroscope’s distributed backend systems, cloud infrastructure, APIs, CI/CD pipelines, observability, and production operations. Build infrastructure for large-scale LLM training, fine-tuning, and inference workloads in partnership with ML researchers. Lead architectural decisions and infrastructure projects, improving system reliability, performance, and scalability while working with Go, GCP, Terraform, PostgreSQL, Temporal, and related technologies.

Build and extend Skydio’s AI coding-agent platform, including agent integrations, MCP servers, sandboxed execution, secure permissions, secrets handling, and auditability. Develop infrastructure for internal tools and agents, collaborate with firmware, autonomy, cloud, and application teams to improve workflows, measure adoption and engineering impact, and drive internal adoption of AI development tools.

Build, automate, and operate scalable AWS infrastructure, including networking, compute, CI/CD, databases, and observability. Develop internal tools and self-service platforms, manage infrastructure with Terraform, collaborate with engineering teams, participate in on-call rotations, and replace repetitive operational work with software and permanent incident fixes.

Build and operate cloud networking and traffic infrastructure across clusters, regions, and clouds. Develop gateways, proxies, controllers, routing automation, load balancing, telemetry, and connectivity systems. Diagnose failures and performance issues across networking layers, improve reliability and efficiency, implement security controls, and partner with infrastructure, security, service, and cloud-provider teams. The role includes production ownership, safe rollouts, on-call participation, and turning operational lessons into durable improvements.

Lead the design, operation, and modernization of large-scale infrastructure environments, including QEMU/KVM virtualization, private cloud, distributed storage, and infrastructure as code. Drive VMware-to-KVM migration, storage platform migration, monitoring, resilience, incident root-cause analysis, and automation. Mentor junior engineers, support CI/CD infrastructure, participate in on-call rotations, and provide technical leadership across distributed teams.

Build and operate Python backend services and automated pipelines for securely transferring model weights, configurations, code, and container images to strategic partners. Responsibilities include implementing validation and business logic, integrating source control, storage, and build systems, improving reliability through testing and monitoring, debugging cross-service issues, and collaborating with research, security, infrastructure, and partner engineering teams.

Design and own developer and test infrastructure for production-like environments. Build CI/CD pipelines, deployment automation, data-generation tools, workload simulations, and infrastructure supporting integration, load, performance, and correctness testing. Enable AI coding agents to test and validate code autonomously while improving engineering velocity, reliability, scalability, and cost efficiency. Collaborate with engineering teams to remove development bottlenecks and scale testing systems.

Owns production infrastructure across Kubernetes, CI/CD, Linux systems, virtual machines, and AI accelerator environments. Responsibilities include incident response, troubleshooting, automation, monitoring, alerting, patching, upgrades, certificate renewals, capacity checks, runbook development, and on-call support. The engineer collaborates across IT and product software teams and contributes to infrastructure design and build work.

Designs, deploys, and manages secure, scalable GCP infrastructure using Terraform. Builds CI/CD pipelines, automates infrastructure and application delivery, optimizes cloud performance and costs, and maintains reliability through monitoring and incident management. The role requires deep GCP and Terraform expertise, familiarity with CI/CD tools, and knowledge of containers, Kubernetes, zero-trust security, IAM governance, and cloud compliance.

Owns the reliability, performance, and operation of a high-density GPU compute cluster. Responsibilities include Linux administration, cluster monitoring, GPU deployment and driver management, kernel and hardware debugging, network security, identity and distributed storage administration, and maintenance of CUDA, ROCm, PyTorch, JAX, vLLM, and related ML infrastructure. The role also handles incident response, vendor coordination, performance tuning, and automation for large-scale AI infrastructure.