Top Remote Platform Engineer Jobs

Design and implement full-stack applications and AI agents for the GenAI platform, ensuring rapid development and deployment across critical industries. Collaborate with teams to deliver secure and reliable cloud-native systems.

Join Sei Labs as a Senior Engineer to build scalable blockchain infrastructure, focusing on CI/CD, observability, and security in a decentralized finance environment.

Lead cloud-native platform engineering initiatives: migrate Jenkins pipelines to Harness, move GCVE/on‑prem workloads to GKE, implement GitOps, IaC (Terraform/Ansible), enforce cloud governance and security, build observability and scalable GKE infrastructure, and coach teams on agile and best practices to improve developer productivity.

Design, build and maintain Microsoft Cloud applications using Power Apps/Pages and Azure services. Implement Entra ID authentication, Azure Functions/App Services, Logic Apps and Blob storage. Create Azure Data Factory pipelines and APIs (REST/GraphQL), integrate external services and LLM data pipelines, and ensure performance, security, and scalability while collaborating with customers to turn requirements into streamlined apps.

Develop and maintain Power Platform (Canvas and Model-driven) apps, Power Automate workflows, and Dataverse models; administer and enhance SharePoint Online sites and web applications; integrate solutions with Microsoft 365, Teams, and SQL Server; ensure federal compliance (FISMA, NIST, Section 508), support ATO processes, provide tier-2 support, testing, release management, and maintain technical documentation.

Lead architecture and technical direction for the Variant Knowledge Platform: define data models, design versioned REST APIs (Okta-secured), drive pipelines that convert bioinformatic data to variant/sample-level truths, enable real-time multi-tenant operation, lead cross-team programs and large data migrations, set operability practices, mentor engineers, and align platform strategy with product, curation, and clinical stakeholders.

Provide expert-level technical support for NVIDIA DGX compute/GPU platforms: triage and resolve hardware and software issues on multi-distro Linux, debug installations and interoperability, coordinate with engineering/marketing, create KB articles, and improve support processes. Interact directly with customers via phone/email/conference and apply AI tools for debugging and documentation.

Maintain and expand the companys foundational AI platform codebase; support project teams to increase reuse (50-70%); fold successful project work back into the platform; address bugs and performance issues; create training, documentation, and onboarding; provide pairing and code reviews; and collaborate with sales and delivery teams on platform capabilities and project requirements.

Own and evolve the platform-as-product used by engineering teams: improve reliability and observability, build test infrastructure and CI/CD tooling, optimize infrastructure cost and strategy, maintain infrastructure-side compliance (SOC 2/HIPAA), and serve as first-response for platform on-call incidents.

Join an early-stage platform team to scale and mature a mortgage origination platform. Work across the stack to improve distributed systems, performance, observability, and infrastructure tooling, and help define engineering standards and frameworks for growth.

Build and own enterprise-grade organization management, RBAC/authorization, audit logging, enterprise policies, admin APIs, and compliance features. Design scalable, secure multi-tenant platform primitives and tooling to support large organizations.

Design and build high-throughput reconciliation systems and data pipelines. Implement real-time (Flink) and batch (Hive) workflows, write complex SQL for validation and anomaly detection, collaborate with Finance/Risk/Product on reconciliation rules, optimize for low latency, and leverage AI/LLM tooling to automate triage and improve operations.

Design and implement a scalable Elasticsearch-based analytics platform integrated with an Oracle data warehouse. Architect data models, ingestion/CDC pipelines, index/shard strategies, and monitoring. Optimize cluster, queries, and caching for sub-second dashboard performance, perform load testing and capacity planning, and produce operational documentation and SLAs.

Design, build, and operate secure, compliant AWS environments using Terraform and automation. Build CI/CD pipelines, security automation, observability, and support containerized and serverless workloads. Contribute to ISO 27001/SOC 2 compliance, create developer tooling, and troubleshoot complex platform issues in a distributed team.

Design, build, and operate secure, highly available AWS infrastructure using IaC. Own cloud networking, container platforms, CI/CD, observability, incident response, runbooks, and SIEM integrations. Optimize performance, cost, and reliability, and support customer RFPs on network and infrastructure.

Design, build, and maintain scalable cloud or hybrid infrastructure with automated CI/CD, monitoring, and cloud optimization to ensure 99.9% uptime. Lead migration efforts, implement monitoring and performance strategies, and collaborate with cross-functional teams to maintain platform stability.

Own and scale AWS infrastructure using Terraform; design CI/CD and GitOps pipelines on Kubernetes (Helm, ArgoCD); manage service mesh (Istio), observability, security, capacity planning, cost optimization, and incident response; mentor engineers and document runbooks.

Build and operate Valence's shared platform primitives (auth, routing, LLM gateway, deployment, observability, SLOs) to enable safe, scalable, and compliant delivery of AI-first products. Implement CI/CD gates, progressive delivery, rollback automation, security guardrails, region-aware routing, and developer-facing templates and tooling.

Design, develop, and integrate software, APIs, and automation to improve test platform efficiency. Build CI/CD pipelines, data pipelines, dashboards, and integrations with third-party diagnostic/test tools. Collaborate with test engineers, operations, and vendors to reduce manual work, increase throughput, and provide visibility into test metrics. Support troubleshooting, documentation, and global standardization of integration frameworks.

Build and own Sekai's native Android foundation using Kotlin and modern Android architecture. Improve app shell, lifecycle, navigation, permissions, notifications, release workflows, and hybrid integration with React Native/Flutter/WebView. Improve reliability, observability, and release quality while partnering with Product, Design, Backend, and Mobile teams to ship high-quality consumer experiences.

Design, build, and maintain scalable, secure data pipelines and platforms to acquire, transform, and store large financial datasets. Enable AI/GenAI-ready data foundations for model training, inference, retrieval, and RAG workflows. Collaborate with cross-functional teams, ensure data quality, governance, observability, and compliance, and support production deployments and troubleshooting.

Lead frontend platform architecture across web and mobile: design and evolve design systems, component libraries, build tooling, accessibility, internationalization, and developer experience. Partner with backend teams on GraphQL/Python, maintain security and compliance, mentor engineers, drive cross-team initiatives, and deliver scalable, high-quality frontend foundations used by multiple product teams.

Lead architecture and implementation of a large-scale analytics stack: design foundational pipelines, establish modeling/orchestration standards, integrate AI-assisted engineering tools, translate business questions into version-controlled data models, partner with stakeholders to define metrics and data contracts, migrate logic into maintainable pipelines, and optimize cloud warehouse performance for scale.

Own and build the shared AI/ML platform: audit and evolve training and serving pipelines, implement training infrastructure on Databricks, enable experiment tracking and model registry, provide low-latency serving and batch scoring, build ML observability (drift, accuracy, business metrics) with Grafana/Prometheus, optimize cost/performance, mentor engineers, and drive AI-native tooling adoption.

Own and evolve Cint's shared AI/ML platform: audit existing pipelines, build training infrastructure (Databricks/Unity Catalog), experiment tracking, model registry, serving, monitoring, cost controls, and mentor engineers to enable rapid, reproducible ML lifecycle and production-grade model operations.