Top Remote Platform Engineer Jobs

Lead platform and infrastructure engineering to improve stability, developer productivity, CI/CD, observability, and shared libraries. Deliver platform projects, mentor engineers, own production availability and on-call, and drive platform decisions and best practices across the org.

As an ML Engineer at Luma AI, you will design high-performance model serving pipelines, manage GPU resources, and optimize CI/CD for large-scale AI systems.

The Senior Software Engineer will build GPU-accelerated compute platforms for AI workloads, focusing on orchestration, resource management, and performance optimization.

This role involves designing and implementing infrastructure systems for AI workloads, focusing on orchestration, automation, APIs, and compliance in a cloud-native environment. Collaboration across teams is essential for project success.

Build and implement a software-defined networking platform for high-performance AI workloads, ensuring network isolation and high-speed connectivity for research and infrastructure teams.

The Technical Engineer will manage system administration of the Starburst platform, collaborate on solutions across teams, and ensure efficient operational support.

The Staff Software Engineer will lead the architecture and development of a real-time content platform, working on both backend and frontend systems while mentoring team members and collaborating with product and design teams.

The Cloud Platform Engineer will design and implement cloud infrastructure, automate deployments using Terraform and Argo, develop serverless applications, and collaborate with teams to maintain robust cloud services.

Serve as the technical lead for Acceldata's Hadoop observability and open data platform in pre-sales: deliver demos, design solutions, run POCs, craft technical proposals/SOWs, collaborate with sales/product/engineering, and support closing deals while educating internal teams and producing technical documentation.

Own and evolve Syndi, an agent runtime powering in-product chat and integrations. Design, ship, and operate core runtime surfaces (agent loop, tool execution, memory, context), build eval systems, ensure observability and reliability, review consumer integrations, and implement compliance and legal requirements for production LLM systems.

Build and maintain Back of House data delivery and related BOH projects using AWS serverless technologies. Write code and unit tests, collaborate with SRE/QE/security/product teams across Yum! Brands, document data flows, and improve tooling and processes to increase restaurant operational efficiency and data integrations.

Build and maintain full-stack product features, backend services, APIs, data pipelines, and AI integrations to transform customer interaction data into AI-powered experiences. Collaborate with cross-functional teams to design, test, and support production systems, internal tools, and user-facing interfaces. Own ambiguous problems end-to-end and raise engineering quality across the data and AI platform.

Embedded with strategic customers, own end-to-end design, build, and production rollout of cloud infrastructure for large-scale GPU/HPC AI workloads. Build compute orchestration, platform services, onboarding sandboxes, and reliability/security tooling. Turn field learnings into reusable platform capabilities and partner with Product and Engineering to productize them.

Own and improve the end-to-end developer experience for AIMS ML teams: local/remote dev environments, build/test infrastructure, CI/CD, and internal platforms. Design, build, and operate large-scale build and CI systems, remove developer friction, instrument workflows, drive adoption, and set technical standards. Partner with ML researchers to prioritize productivity investments and evaluate/integrate GenAI-powered developer tooling with safety guardrails.

Lead strategy and roadmap for an enterprise developer platform and AI engineering capabilities. Define CI/CD, cloud, and security standards; drive AI-enabled developer tooling adoption; partner across engineering, security, and cloud teams; manage global senior leaders; own platform performance, budgets, vendor decisions, and continuous improvement.

Develop production-grade AI agents for enterprise customers. Design and build LLM-powered systems, integrating workflows, evaluation, and performance standards. Collaborate closely with customers and teams to ensure reliability and effectiveness in real-world applications.

Contribute to the development of Waabi World, improve simulation scalability, and design orchestration software for autonomous vehicle simulations.

Design, build, and evolve customer-facing backend services and public APIs; own features end-to-end from design through rollout; create technical design documents; ensure services are observable, resilient, and usable across multiple products; collaborate closely with Product and Experience teams to prioritize and ship iterations.

Design and build reusable platform components, integration frameworks, and tooling for healthcare interoperability. Implement REST APIs, RPA automation (Python, Selenium, OpenCV), FastAPI/React full-stack apps, and deploy/manage services on Azure using IaC and CI/CD while ensuring HIPAA compliance and strong developer documentation.

Design, build, and operate AWS-based cloud platforms and Amazon EKS Kubernetes environments. Implement Infrastructure-as-Code (Terraform), CI/CD and GitOps pipelines, monitoring/observability, security controls, and self-service platform capabilities. Partner with compliance, security, and engineering teams to support GMP and non-GMP workloads, incident response, and continuous platform improvements.

As a Software Engineer at Oncora, you will develop and maintain our data platform, integrating various data sources, optimizing data infrastructure, and enhancing de-identification capabilities for machine learning and clinical research.