Top Cloud Engineer Jobs in Seattle, WA

Designs and develops highly available cloud services for AI inference workloads. Responsibilities include building Kubernetes controllers and platform capabilities for deployment, scheduling, scaling, recovery, upgrades, observability, and lifecycle management. The role leads production readiness reviews, resolves complex infrastructure issues, improves reliability and performance, drives architecture and design reviews, mentors engineers, and influences technical direction across teams.

Lead the architecture and development of highly available cloud services for AI inference. Build Kubernetes controllers and platform capabilities for workload scheduling, scaling, recovery, deployment, and lifecycle management. Improve reliability, observability, performance, and resource efficiency through production readiness reviews and incident-driven improvements. Guide complex technical initiatives, mentor engineers, resolve infrastructure issues, and align architecture across AI compute, runtime, and product teams.

Lead the design, development, testing, and deployment of large-scale cloud infrastructure automation software for ServiceNow’s global platform. Build reliable distributed systems, improve observability and resilience, develop automated testing and CI/CD practices, modernize platform capabilities, and mentor engineers. Collaborate with product managers, architects, stakeholders, and distributed engineering teams while applying AI-assisted development and reliability engineering techniques.

Build and operate CoreWeave’s multi-cloud internal infrastructure across GCP, Azure, and AWS. Manage cloud foundations, IAM, networking, Terraform infrastructure as code, monitoring, logging, CI/CD, backups, disaster recovery, and production reliability. Troubleshoot complex infrastructure and application issues, support cloud migrations and acquisitions, implement secure architecture patterns, and contribute to incident response and root-cause analysis. Mentor junior engineers and communicate technical decisions across teams.

Support enterprise customers and partners integrating applications with Wasabi Cloud. Diagnose, research, reproduce, and report defects; test storage services with third-party applications; validate interoperability using APIs and SDKs; investigate S3 protocol behavior; and collaborate with sales, development, QA, product, and support teams.

Cloud Engineer Interns will support cloud solution design, architecture, implementation, monitoring, troubleshooting, and security. They will collaborate with software engineering and cybersecurity teams, provide technical support, and identify performance improvements. The 10-week program includes mentorship, professional development, networking, and community service activities, with potential conversion to a full-time technology development program after graduation.

Administers and monitors cloud, storage, and virtualization infrastructure; troubleshoots incidents; performs storage array maintenance, upgrades, provisioning, replication, and quality assurance. Maintains technical documentation, manages tickets and alerts, supports clients, collaborates across teams, develops recurring-issue solutions, contributes to on-call coverage, and mentors or trains others.

Maintain and improve AWS cloud applications and infrastructure using Terraform, EKS, ECS, Lambda, and CI/CD pipelines. Manage Kubernetes environments, deployments, monitoring, vulnerability remediation, incident response, autoscaling, failover, and disaster recovery. Collaborate with development, operations, and security teams to ensure scalable, secure, fault-tolerant production systems. Participate in 24/7 on-call rotations, automate operational tasks, and maintain recovery runbooks and compliance with RTO/RPO requirements.

Lead the design and implementation of cloud architecture components and deliver low-latency, highly scalable services. Collaborate with desktop agent and AI teams, drive technical decisions across stakeholders, and improve engineering practices through hiring, design reviews, postmortems, code reviews, and mentorship. Apply AI technologies to improve decision-making, workflows, efficiency, and business outcomes while operating resilient, high-volume Tier-1 cloud systems.

Lead the design and implementation of major cloud architecture components and deliver low-latency, highly scalable services. Collaborate with desktop agent and AI teams, drive technical decisions across stakeholders, and improve engineering practices through design reviews, postmortems, hiring, code reviews, and mentorship. Apply AI technologies to improve decision-making, workflows, efficiency, and business outcomes while operating high-volume, resilient Tier-1 cloud systems.

Design, implement, secure, and operate enterprise GCP environments for U.S. federal workloads. Build cloud networking, Kubernetes platforms, Infrastructure as Code, CI/CD pipelines, automation, monitoring, and security controls aligned with federal compliance frameworks. Support ATOs, continuous monitoring, vulnerability remediation, troubleshooting, technical documentation, customer collaboration, and mentoring of junior engineers.

Provide senior-level ownership for AWS cloud platform operations, automation, and reliability. Support infrastructure provisioning, EKS/Kubernetes operations, EC2/AMI lifecycle, observability, incident response, patching, cost optimization, CI/CD automation, documentation, runbooks, and mentoring. Participate in on-call rotation, incident handling, and cross-team collaboration to ensure secure, scalable cloud operations.

Build and operate a hyper-scale data lake and analytics platform: develop Java microservices and Spark/Scala/Flink pipelines, own a new graph database, design ultra-high-scale data platforms, optimize performance and latency, enable efficient querying for analytics and ML, and collaborate on feature design and stability across teams.

Design, build, and operate secure, scalable Azure infrastructure and shared platform services. Develop landing zones, networking, identity, governance, PaaS, containers, CI/CD pipelines, and Infrastructure-as-Code frameworks using Terraform, GitHub Actions, or CDKTF. Create reusable deployment patterns and automation, apply security and compliance controls, and implement monitoring and operational readiness. Partner with engineering, data, security, and risk teams to deliver foundational cloud capabilities and enable enterprise-wide Azure adoption.

Implement and support AWS cloud infrastructure, platform services, and Infrastructure as Code with Terraform. Build CI/CD pipelines using GitHub Actions, administer AWS services including EKS, Lambda, S3, IAM, CloudWatch, and VPC, and automate provisioning, monitoring, and maintenance. Troubleshoot incidents, optimize performance, monitor platform health, collaborate on secure scalable solutions, and maintain technical documentation. The role is fully remote, requires U.S. citizenship, and may involve periodic travel and after-hours mission-critical support.

This role involves developing and implementing testing frameworks for ensuring reliability and performance of AI security controls across platforms. The engineer will expand test coverage and contribute to quality metrics for AI models.

Lead the design and implementation of cloud architecture to support CrowdStrike's mission in cybersecurity, ensuring scalability and resilience of services.

Migrate applications to Microsoft Azure using IaaS, and refactor or rewrite components to leverage PaaS services. Work involves cloud architecture, implementation of Azure infrastructure, and application modernization to optimize cloud-native services.

Lead cloud networking architecture across AWS/Azure/GCP, define reusable network standards, manage technical risk and remediation, drive compliance and incident response, establish policy-as-code guardrails, mentor engineers, and coordinate cross-functional solution designs emphasizing security, resilience, and performance.

Designs, deploys, and operates production service mesh platforms, primarily Istio and Linkerd, across Kubernetes environments. Responsibilities include mesh adoption, mTLS, traffic policies, Envoy configuration, networking, ingress, CNI, certificate lifecycle management, observability, distributed tracing, and troubleshooting across application and control-plane layers. The engineer will also build automation in Go or Python, support multi-cluster deployments, and collaborate with application teams on pragmatic service mesh adoption.

Lead the architecture, deployment, operation, automation, and security of Microsoft’s global wired access and out-of-band networks. Responsibilities include switching and routing engineering, multi-site migrations, network automation, observability, AI-assisted tooling, incident leadership, reliability improvements, governance, vendor coordination, design reviews, and mentoring. The role includes participation in a 7x24 on-call rotation and requires expertise in enterprise networking, security architecture, and service operations.

As a Senior Cloud Support Engineer, you'll provide high-level support for GPU workloads, mentor team members, resolve complex technical issues, and enhance customer satisfaction through technical expertise and problem-solving.

Designs, secures, operates, and supports multi-account cloud infrastructure across AWS, Azure, and GCP. Responsibilities include AWS networking, Terraform infrastructure as code, GitHub Actions CI/CD pipelines, identity and access management, cloud governance, observability, incident response, disaster recovery, cost optimization, and compliance controls. The role also develops automation, maintains technical documentation, and provides after-hours support when needed.

Develop and maintain secure, scalable cloud-based backend platforms, APIs, and data pipelines supporting AI-enabled healthcare applications. Process large clinical data objects, integrate AI models, contribute to web applications, conduct code reviews, write automated tests, validate architectural approaches, and collaborate with product, QA, security, regulatory, and software engineering stakeholders in a regulated environment.

Develop secure, scalable backend APIs, cloud data-ingestion pipelines, and distributed systems supporting AI-enabled healthcare applications. Build systems handling clinical data such as images, videos, STL files, and CT scans; integrate AI models; contribute to web applications; conduct code reviews and automated testing; and collaborate with product, security, regulatory, QA, and engineering teams in a regulated environment.