Top Remote Platform Engineer Jobs

Design, build, and maintain scalable, resilient data platform services for data integration, event processing, and orchestration. Improve data availability, discoverability, dependability, and security tooling while collaborating across cross-functional teams and delivering production-grade solutions at scale.

The Senior Platform Engineer at EDO will focus on enhancing internal platform capabilities using AWS services, Terraform, and improving team workflows to ensure reliable and efficient infrastructure.

Lead technical strategy and modernization of a high-scale communications platform. Improve reliability, observability, and operations across Kubernetes and multi-cloud environments. Drive migration planning, IaC adoption, incident response, architecture standards, and cross-functional engineering coordination while maintaining production stability.

Lead architecture and modernization of the Composer CMS platform, decoupling legacy dependencies while maintaining stability. Improve scalability, reliability, observability, and operational resilience for containerized, distributed production systems. Establish engineering standards, mentor engineers, run architecture reviews, and support cross-functional technical decisions using AI-assisted development tools.

Build integrations that discover, identify, and govern AI agents across third-party platforms such as Salesforce Agentforce, Microsoft, AWS, and Google Cloud. Retrieve native identity signals, integrate them with Delinea’s identity layer, and govern agents through provider APIs and attestation. Improve shared discovery capabilities while using connector patterns, OAuth, token exchange, and event-based ingestion. The role requires substantial backend engineering experience, strong integration skills, and familiarity with cloud, AI agent, security, or identity ecosystems.

Lead design, implementation, and operation of Signifyd's GCP/Kubernetes cloud platform. Architect scalable, secure infrastructure, embed AI-driven automation, own SLOs and incident response, improve developer experience via CI/CD/GitOps tooling, mentor engineers, manage cloud capacity/FinOps, and build observability and security into the platform.

Senior Software Engineer joining Fetch’s Data Platform team to architect and evolve scalable data pipelines, governed data access, delivery infrastructure, and partner integrations. The role owns ambiguous technical problems, leads multi-system initiatives and migrations, improves reliability and engineering efficiency, shapes technical direction, collaborates across teams, and mentors engineers. Candidates need strong backend or platform engineering experience, data infrastructure knowledge, cross-team leadership, operational judgment, and excellent communication skills.

Design and build scalable training platform infrastructure for large distributed ML model training. Improve performance, reliability, and cost-effectiveness of training jobs. Build APIs/UX for ML engineers, diagnose GPU/communication/memory bottlenecks, and implement observability, fault tolerance, and on-call practices while partnering with ML researchers and infrastructure teams.

Build and operate next-generation ML data and feature infrastructure, including near-real-time feature computation engines, feature stores, and embedding retrieval systems. Scale data processing, storage, and serving for high-throughput training and low-latency inference. Collaborate with ML practitioners and AI Platform teams to improve feature discovery, sharing, and practitioner productivity.

Design, build, and operate cloud-native, large-scale distributed data infrastructure (Spark, Presto/Trino, Druid, Iceberg). Improve performance, scalability, and reliability, collaborate cross-functionally, and contribute to open-source projects.

Build and operate scalable, fault-tolerant distributed data infrastructure and platforms. Design and implement RESTful services, tackle multi-threading and reliability challenges, partner cross-functionally to enable data movement, storage, schema management, and developer experience at large scale.

Design, implement, and maintain high-performance cloud gaming software stacks across the application pipeline, including hardware-accelerated video/audio/data processing, media encoding/decoding, graphics APIs, and network transport. Optimize local and end-to-end system performance, work across complex codebases and hardware platforms, collaborate across teams, and take ownership from conception to production.

Lead design and execution of a modernized, Python-native AI/ML platform for AIMS: define architecture, drive migration, build migration tooling, ensure scalability, observability, cost optimization, and reliability, prototype GenAI operational tooling, and set org-wide technical standards.

Design, productionize, and deploy machine learning forecasting models for ad inventory and campaign performance in low-latency, real-time advertising environments. Build scalable simulation, budgeting, and pacing systems; collaborate with cross-functional teams to deploy models at scale and optimize ad monetization.

Design, develop, and deploy AI-enabled automation using Power Platform and Copilot Studio. Build Power Apps, Power Automate flows, Dataverse solutions, conversational agents, API integrations, and enterprise-grade authentication. Define architecture, governance, ALM, environment standards, and mentor citizen developers while collaborating with stakeholders and supporting operational monitoring.

Build and scale AI data and ML infrastructure: evaluation systems, fine-tuning pipelines, agent-first product surfaces, high-throughput data workflows, and integrations of new models into production.

Build and operate the internal Developer Platform: improve monorepo CI/CD, scale agentic AI platform (observability, RAG, context engineering), consolidate build systems, automate developer toil, and drive DORA-aligned delivery across teams through design, code reviews, and platform roadmaps.

Design, build, and operate multi-cloud platform infrastructure, CI/CD, Kubernetes clusters, networking (including Cato/SASE), and internal developer tooling in Go/Python. Drive enterprise architecture, reliability targets, RBAC/secrets governance, integrate AI tooling, consolidate systems, and partner with product teams to increase developer velocity and reduce toil.

The Software Engineer will build and own features for the AI-driven matching and screening platform, focusing on data structuring and full-stack development. Collaboration with users and maintaining high quality through testing is essential.

Develop and operate a system for argumentation related to AI safety, utilizing ontologies and knowledge graphs while collaborating with various stakeholders.

As a Software Engineer, you will design and implement scalable infrastructure systems for AI-powered security solutions, optimize performance, and improve deployment practices across cloud environments.

As a Platform Engineer at Revic, you'll design and maintain scalable cloud infrastructure for AI systems, manage CI/CD pipelines, improve developer experience, and reduce operational friction while ensuring reliability and performance.

Lead design and scaling of a high-performance, data-intensive storage layer for network telemetry. Co-own multi-year roadmap, collaborate with product/support/sales, and solve challenging distributed storage and query-performance problems at large scale.

The Systems Engineer will architect and implement solutions for queueing systems and state stores, improve throughput and latency, and collaborate with teams to enhance the user experience.

Lead design and implementation of products, mentor engineers, drive innovation, and build scalable data solutions using modern tech stack.