Top Remote Platform Engineer Jobs

As a Senior Backend & Platform Engineer, you'll design and operate critical systems in identity management, financial operations, and blockchain infrastructure while leading projects and mentoring engineers.

The Platform Engineer will develop, maintain, and automate the platform environment, ensuring efficient integration and problem-solving, while guiding junior engineers.

As a Platform Engineer, you will automate production environments, validate implementations, problem-solve independently, and facilitate communication between teams.

As a Senior Platform Engineer, you will design, implement, and maintain data models and infrastructure while improving data quality and scalability. You'll collaborate across teams and mentor fellow engineers to enhance data usability and reliability.

Deliver, automate, and sustain Keeper platform deployments across IL5/IL6 and classified U.S. Government environments. Build CI/CD pipelines, automate infrastructure (IaC), maintain hardened configurations, support releases and incident response, and produce audit evidence. Troubleshoot production issues, implement observability, partner with engineering and security teams, and ensure compliance with federal security frameworks.

Build and operate the multi-tenant platform layer for a GPU cloud service. Responsibilities include Kubernetes-based orchestration, tenant isolation, platform APIs and tools, GPU cluster automation, infrastructure as code, reliability and observability partnerships, customer issue support, environment templates, rollout tooling, architecture reviews, and reducing operational toil.

Owns infrastructure, deployment automation, and security for a serverless AWS loan-servicing platform. Responsibilities include designing fault-tolerant infrastructure, building infrastructure-as-code frameworks, automating secure deployment pipelines and security controls, monitoring systems, troubleshooting performance issues, supporting DevOps tooling, and establishing auditable build and release standards. The role also requires cross-functional collaboration, mentoring, stakeholder education, and independently solving complex technical problems in a regulated financial-services environment.

Lead and evolve the core platform architecture powering n8n: design scalable distributed execution, persistence and data foundations; define platform interfaces; drive RFCs and migrations; enable and mentor engineering teams; ensure reliability, tenant isolation, and operability across cloud and self-hosted deployments.

Design, build, and operate Kubernetes cluster management tooling and developer-facing workflows. Deliver compute capabilities (jobs, cron, deployments, EFS, right-sizing), automate toil, improve observability and incident response, and partner with Security/Reliability teams. Apply AI tooling to improve infrastructure automation and developer productivity.

As a Senior Software Engineer on the Logistics Platform team, you will enhance logistics systems by building APIs, improving data quality, and partnering with cross-functional teams to solve complex problems, ultimately improving user experiences and operational outcomes.

Design, build, and operate ML infrastructure for training, evaluation, deployment, and inference. Improve reliability, scalability, latency, throughput, and cost. Create pipelines, observability, benchmarking, and tooling to enable fast experimentation and productionization of models while diagnosing regressions and bottlenecks.

As an Agentic Platform Engineer, you will design and manage core platform services and tools for high-scale distributed systems, focusing on Kafka and AWS environments, while delivering automated workflows across OnePay's products.

Own and implement platform initiatives to improve scalability, reliability, and developer experience. Automate infrastructure with IaC, operate Kubernetes and CI/CD pipelines, build developer tools, monitor platform resilience, participate in incident response, and influence architecture and processes as you grow.

Lead design and delivery of a reliability platform for production systems. Own quarterly goals, guide engineers through ambiguity, collaborate with PM/design/analytics, monitor and operate services (on-call), set quality and code standards, and mentor teammates. Integrate AI/LLM tooling to improve automation, debugging, and service health.

Lead endpoint and IT operations across global offices and remote field sites: design zero-touch provisioning, manage Jamf/Intune policies, build fleet monitoring, own software procurement and license optimization, administer Okta and Google Workspace, automate onboarding/offboarding, supervise IT support staff, and collaborate with security, infrastructure, legal, and finance to run reliable, compliant IT for distributed exploration teams.

Build and maintain cloud-native platform infrastructure and Kubernetes clusters, develop IaC and CI/CD pipelines, support IAM and monitoring, manage certificates and container security, participate in on-call incident response, and document runbooks and standards while mentoring junior engineers.

Lead Pinterest’s technical strategy and roadmap for scalable big data and AI infrastructure. Build frameworks for compute, job, resource, scheduling, and shuffle management across petabyte-scale datasets. Partner with internal customers, provide company-wide technical leadership, and improve data processing reliability, speed, and efficiency.

Design, build, and maintain scalable AWS infrastructure using IaC. Improve CI/CD pipelines, implement monitoring and observability, automate routine infrastructure tasks, manage cross-account AWS environments, and advise engineering teams on best practices to ensure reliability, security, and performance.

Build, operate, and extend data platform and application-layer services enabling secure, self-service data applications at scale. Implement provisioning, CI/CD, access control, integrations, observability, automation, and incident response while contributing to semantic layer and AI-ready tooling roadmaps.

Design and implement AI/ML platforms, establish secure connectivity, build CI/CD pipelines, integrate conversational AI, and ensure security compliance in insurance processes.

The Staff Platform Engineer will lead the design and operation of ad-serving platforms, ensure reliability, and mentor teams while implementing automation and observability practices.

Build and operate multicloud Kubernetes infrastructure and platform capabilities, including cloud foundations, networking, identity, cluster lifecycle, disconnected deployments, packaging, GitOps delivery, infrastructure as code, observability, upgrades, and incident response. Partner with engineering teams to provide reusable self-service infrastructure primitives across commercial, government, secure, classified, and disconnected environments.

Build and operate multicloud Kubernetes infrastructure and platform capabilities across commercial, government, classified, and disconnected environments. Responsibilities include cloud foundations, networking, identity, cluster lifecycle, packaging, GitOps delivery, infrastructure-as-code, policy enforcement, staged rollouts, observability, incident response, and backup/recovery. The engineer will also create self-service infrastructure primitives for internal engineering teams and support reliable fleet-scale deployments.

Design and build scalable developer-platform architecture, tooling, frameworks, CI pipelines, testing systems, and deployment processes. Lead initiatives that improve engineering velocity, reliability, code quality, and customer experience. Drive adoption of AI-assisted development tools, optimize development workflows, modernize legacy patterns, and establish release safeguards such as canaries, traffic replay, and enterprise feature bundling.

Design, secure, and scale GCP cloud infrastructure supporting event-driven services, AI models, and automated releases. Maintain infrastructure as code and CI/CD automation, manage access controls and encryption, remediate penetration-test and vulnerability findings, and own monitoring, dashboards, on-call response, incident management, and performance improvements.