Top Remote Platform Engineer Jobs

Design, build, and maintain application hosting infrastructure on Kubernetes in GCP. Implement infrastructure as code, CI/CD pipelines, cloud security and CVE remediation, monitor and optimize performance and costs, and support internal platform users.

Lead design and implementation of core platform infrastructure for an Agentic AI platform. Build high-performance Rust systems, support production deployments, collaborate with ML engineers, design scalable data architectures, troubleshoot performance and scalability issues, and cultivate a collaborative, inclusive engineering culture.

Own and scale Adobe Experience Platform and Real-Time CDP implementations. Design data collection architecture using Web SDK, Edge Network, and datastreams; govern XDM schemas, identity, datasets, and data quality. Develop tagging, CJA connections and views, audience activation, privacy frameworks, and event-driven data layers. Troubleshoot ingestion and identity issues, integrate Adobe ecosystem tools and downstream systems, and collaborate with stakeholders on scalable technical solutions, governance, documentation, and enablement.

Join Archy as a Senior Platform Software Engineer to enhance dental practice management through a scalable SaaS solution, focusing on cloud infrastructure, CI/CD pipelines, and AI integration.

Design and scale high-throughput, low-latency backend systems powering Fetch’s advertising platform. Own architecture across ad selection, targeting, delivery, attribution, and measurement services; improve reliability, observability, performance, and resilience; lead cross-team technical initiatives and migrations; establish engineering standards; resolve complex distributed-systems problems; and mentor senior engineers across Ads, Platform, Data, ML, and Product teams.

Lead the migration of Vanta’s resource data platform from MongoDB to schema-aware PostgreSQL while maintaining API compatibility and data integrity. Design high-throughput Kafka and S3 ingestion pipelines, eventual-consistency strategies, query infrastructure, tenant isolation, and reliable distributed systems. Set architectural direction across storage, caching, and streaming technologies; mentor engineers; drive cross-team technical roadmaps; and improve reliability, observability, and operational excellence.

Architect and develop scalable backend microservices for payments, disbursements, or governance, risk, and compliance. Design secure, high-performance infrastructure handling millions of daily requests, integrate Google Cloud services, implement financial workflows, and collaborate with product, operations, and compliance teams. Mentor junior engineers, promote engineering best practices, and continuously improve platform capabilities using analytics and user feedback.

Leads architecture, development, and technical strategy for omnichannel Order Management capabilities, including order orchestration, inventory, fulfillment, returns, and post-purchase experiences. Designs scalable API-first, event-driven microservices and integrates OMS with commerce, ERP, WMS, payments, logistics, and customer-service systems. Establishes engineering standards, reliability practices, testing, observability, and performance strategies while mentoring engineers and driving AI-assisted development improvements.

Lead architecture and implementation for a secure distributed data platform runtime. Design Go-based concurrency, subprocess supervision, inter-service protocols, distributed persistence, and resilient processing pipelines. Debug complex cross-process and network issues, define testing standards, conduct end-to-end integration and resilience testing, participate in on-call rotations, and lead incident post-mortems. Collaborate with product, engineering, and customer stakeholders to refine requirements and deliver production-ready capabilities. Requires up to 25% international travel to the Middle East.

Design and build distributed systems, high-performance APIs, real-time data pipelines, and intelligent LLM-powered applications processing billions of events daily. Develop advertising, identity, and intent platform capabilities using streaming, batch, and large-scale data technologies. Own system quality, scalability, performance, and observability while collaborating with product managers, data scientists, and engineers. Provide technical leadership and mentorship across initiatives involving ad infrastructure, identity resolution, behavioral analytics, and applied AI.

Lead development of Luminai’s core platform, including shared frameworks, developer tooling, CI/CD, test infrastructure, observability, reliability, and IDE improvements. Architect high-performance backend systems, remove engineering bottlenecks, and establish secure defaults for authentication, authorization, and secrets management. Drive foundational technical initiatives and improve developer experience across the engineering organization.

Design, build, and maintain Luminai’s core platform infrastructure, backend services, shared libraries, internal APIs, and deployment systems. Lead projects that improve scalability, reliability, developer workflows, CI/CD, testing, and local development. Strengthen production systems through secure authentication, access controls, secrets management, code review, testing, and maintainable engineering practices.

Build scalable automated solutions for device fleet management, own and optimize MDM platforms, write OS-level scripts for self-healing, gather telemetry to prevent end-user disruption, translate compliance (CMMC) into code-managed baselines, and create dashboards and alerts measuring end-user SLOs.

Build full-stack features and infrastructure analytics products to improve Netflix's cloud and AI efficiency. Design frontends (React/TypeScript), backend services/APIs (GraphQL/Node), shape data models, collaborate with analytics and data engineers, and own product direction from design through implementation.

Technical leader for Platform & Infrastructure building scalable, resilient cloud-native systems to support large AI workloads. Define architecture, mentor engineers, solve systemic infrastructure bottlenecks, design foundational platform services, and collaborate cross-functionally to ensure secure, high-performance operations.

Lead architecture and scaling of cloud-native infrastructure to support large AI workloads. Mentor engineers, decompose complex systems, design foundational platform services, and collaborate with product, research, and security teams to ensure secure, performant, and highly available GPU/ML infrastructure.

Design, build, and operate foundational, multi-cloud platform systems. Own platform strategy, make build vs. buy decisions, write design docs and code, ensure reliability at scale, document decisions and run architectural forums, and improve operational maturity for enterprise-grade SaaS platform services.

Design, build, and own Astronomer’s multi-cloud platform infrastructure. Lead architecture and implementation of production-scale distributed systems, operate Kubernetes clusters under load, write design docs and postmortems, make tradeoff decisions, and drive cross-team technology choices to improve platform scalability, reliability, and developer experience.

Lead design and implementation of Astronomer’s multi-cloud platform infrastructure. Own platform strategy, build production-grade distributed systems (Kubernetes/Go), make architecture decisions, document designs and postmortems, and drive cross-team technical choices to scale a SaaS/PaaS offering for enterprise customers.

Manage model registries, continuous training loops, and A/B testing infrastructure. Deploy agentic models as scalable microservices on Kubernetes and build observability dashboards to track token usage, latency, and agent reasoning paths. Maintain MLOps pipelines and ensure scalable, observable AI infrastructure.

Build and operate MLOps and agentic infrastructure: manage model registries, continuous training loops, and A/B testing; deploy agents as scalable Kubernetes microservices; and create observability dashboards tracking token usage, latency, and agent reasoning.

Own and evolve the AWS-based platform powering product and AI workloads. Design IaC (Pulumi), build CI/CD pipelines, manage observability, respond to incidents, support LLM workflows (Bedrock, SageMaker), and partner with engineering and ML teams to improve reliability, scalability, and developer experience.

Lead platform strategy and architecture to scale backend systems. Improve reliability, observability, and developer productivity. Mentor engineers, drive technical standards, and build cloud-native Django services on AWS with Postgres performance tuning.

As an AI Platform Backend Engineer, you'll design and deploy backend systems utilizing AI for real-world applications, optimize performance, and mentor junior engineers while working directly with clients to address complex challenges.

As an AI Platform Engineer, you will design and develop AI-driven backend solutions, optimize performance, and collaborate with customers and teams.