Top Remote Platform Engineer Jobs

Lead and scale Sully.ai's multi-cloud platform by owning provisioning, reliability, and automated deployments. Implement GitOps and IaC, standardize developer tooling and CI/CD, optimize scalability and costs for AI workloads, and deliver measurable platform and engineering efficiency improvements.

The Staff Software Engineer will design, build, and maintain compliance systems for fraud prevention, managing KYC workflows and regulatory reporting. They will mentor engineers and drive technical strategy while collaborating with various stakeholders.

As a Senior Platform Engineer, you'll design and maintain backend systems, build APIs, manage infrastructure, and ensure reliability of services in a rapidly growing crypto environment.

As a Principal Mobile Engineer at Consensys, you will oversee MetaMask Mobile architecture, lead cross-team initiatives, enhance developer experience, and mentor senior engineers while integrating AI solutions to boost productivity.

Develop, configure, test, and maintain Microsoft 365 solutions using Power Platform and SharePoint Online. Build Power Apps (canvas and model-driven), Power Automate workflows, Dataverse solutions, Power BI reports, SharePoint artifacts, and PowerShell automation. Participate in Agile ceremonies, requirements gathering, code reviews, testing, troubleshooting, documentation, and production deployments while collaborating with senior staff and government stakeholders.

The Data Engineer will design and maintain scalable data pipelines, automate workflows, and enhance data governance while collaborating with cross-functional teams.

Join the Platform SysEng squad to design, build, and operate highly available, low-latency cloud-native infrastructure. Improve platform scalability, performance, and reliability; own SLOs/SLIs, capacity planning, and production operability; collaborate across teams to reduce region build times and ship platform improvements. Work primarily with Go/Python/Shell, Kubernetes, IaC, and observability tools, and participate in on-call rotations.

Build and evolve GoodShip's internal platform to improve developer experience, CI/CD, IaC, observability, data reliability, and automation. Partner with engineering teams to define SLIs/SLOs, implement monitoring and alerting, eliminate bottlenecks, and scale platform operations to enable fast, reliable software delivery.

Build, operate, and own cloud-native backend services and platform infrastructure (primarily in AWS) to enable data pipelines, analytics, and application workloads. Write production Python code, implement IaC (Terraform/CloudFormation), deploy containerized workloads, design observability and CI/CD, participate in on-call rotations, and collaborate cross-functionally to ensure reliability, security, performance, and cost efficiency.

Design, build, and scale GraphQL and gRPC APIs and SQL queries powering the sportsbook marketplace. Own end-to-end feature delivery, performance diagnostics and remediation, release and deployment windows, monitoring in DataDog, and on-call rotations. Mentor peers, draft technical proposals/specs, and improve platform scalability through load testing, tracing, and production hygiene.

Drive architecture and implementation of an internal AI/agent platform: design agent runtimes and SDKs, define eval-driven release gates, safety, telemetry, and AuthX, partner with product teams to integrate reusable capabilities, set standards for prompt management and observability, write and ship production code, and mentor engineers.

As a Principal Software Developer, you will lead the technical direction and implementation of Autodesk's Viewer platform, drive architectural practices, and mentor engineers across teams.

As a Staff Software Engineer, you will design and implement high-volume ETL pipelines, optimize streaming performance, and mentor the engineering team, ensuring robust data infrastructure.

Build and maintain federated identity and authorization platform services for a multi-tenant SaaS environment. Implement integrations (OAuth/OIDC/SAML/JWT), design observable, fault-tolerant backend services in .NET or Python, use AI-assisted development tools, write tests and observability, participate in on-call and mentoring, and produce documentation and tooling to enable product team integrations.

Design, build, and operate production AI platform capabilities and agentic workflows. Collaborate on architecture, write production-quality backend code, mentor developers, troubleshoot production issues, and drive adoption of reusable AI frameworks, MLOps practices, and cloud-native intelligent services across a multi-tenant SaaS dental platform.

Design, build, and operate distributed, data-intensive backend systems and pipelines. Own production data infrastructure (streaming, batch, analytical stores), debug production incidents, participate in on-call rotations, partner with product and frontend teams, write/review architecture and code, and improve observability, reliability, and deployment practices.

Build and operate the platform: manage EKS/Kubernetes, implement GitOps (ArgoCD), maintain CI/CD (GitHub Actions), define SLIs/SLOs, lead incident response/on-call and post-mortems, design observability (Datadog, Sentry, CloudWatch, Grafana), automate infra with IaC (Terraform/CloudFormation/Crossplane), write Python tooling, and shape platform architecture and self-service workflows.

Design, build and maintain scalable, auditable analytics-ready data models (primarily in dbt) for PBM and care navigation. Implement data quality checks, CI/CD, documentation, pipeline orchestration, and partner with stakeholders to enable self-service analytics and AI-enabled workflows.

Lead operational excellence for enterprise AI/ML platforms: ensure reliability, scalability, observability, governance, and deployment readiness. Build automation, CI/CD, IaC, monitoring, and model lifecycle processes. Serve as senior escalation for incidents, drive root cause analysis, mentor engineers, and partner across Data, Infrastructure, Security, and Product teams to enable production AI workloads and generative AI adoption.

Design and evolve enterprise platform architecture, self-service provisioning, and automation. Implement Azure policy-as-code and Ansible automation, govern Kubernetes/Helm platforms, observability, SLO/SLI, incident response, multi-region strategies, AI/ML infrastructure, and mentor engineers.

Design, develop, and deploy Power Platform solutions on Dataverse, including Power Automate, Power Fx, C# plugins, JavaScript, Dual Write, and Power Apps. Troubleshoot Dataverse/Dynamics CE issues, manage small projects and offshore development, build integrations and data migrations, maintain client relationships, and follow standards and project timelines.

Build and scale a growth data platform: design queues and workers for enrichment, routing, assignment, and activation; integrate CRM, ads, intent, and enrichment vendors; convert experiments into reusable platform primitives; and debug production issues across Snowflake, dbt, Dagster, AWS, vendor APIs, webhooks, and downstream systems.

Design, build, and scale backend microservices for Payments, Disbursements, or GRC squads. Implement secure, high-performance payment and disbursement workflows, KYC/compliance systems, and cloud-native infrastructure. Collaborate cross-functionally, mentor junior engineers, and iterate using analytics, feature flags, and gradual rollouts to support millions of daily requests.

Design, build, and maintain scalable, reliable data systems and pipelines. Partner with Product, Sales Ops, and Finance to deliver analytics and self-service tooling. Maintain SLOs, improve pipeline reliability, implement testing and documentation, and contribute to data platform strategy and operations.

The Senior Platform Engineer will enhance software delivery by developing internal tools, managing CI/CD infrastructure, and improving developer workflows. Collaborating closely with teams, the engineer will contribute to architectural decisions, participate in on-call rotations, and ensure system reliability.