Top Remote Infrastructure Engineer Jobs

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.

The role involves leading engineering efforts for ML infrastructure, optimizing distributed training, and enhancing AI platform efficiency in drug discovery.

The Lead Infrastructure and Reliability Engineer will enhance GPU operations, define scalability strategies, and develop organizational strengths in a high-demand AI infrastructure setting.

The Senior Infrastructure Engineer will design and implement a high-reliability, high-throughput advertising platform, focusing on infrastructure, technical leadership, and incident response management.

Design and build Agora's internal platform, focusing on reusable abstractions, internal services, and enhancing developer experience through scalable systems and engineering standards.

Design, build, and operate scalable AWS-based platform infrastructure for data processing. Improve pipeline automation, monitoring, security, and reliability. Lead CI/CD, IaC (Terraform/Scalr), network design, and incident response; collaborate with cross-functional teams and participate in on-call rotation. Integrate AI tools to streamline development and troubleshooting.

Designs, deploys, integrates, monitors, maintains, and troubleshoots storage and IT infrastructure, including SAN, NAS, object storage, VMware, networking, backups, and disaster recovery systems. Implements automation, security controls, patches, and system upgrades while maintaining documentation and compliance. Collaborates with cross-functional teams, participates in incident response and recovery planning, supports system rollouts, and mentors junior engineers. Requires occasional after-hours work and on-call availability for critical incidents.

Designs, configures, and maintains IT systems for performance, availability, scalability, and security. Monitors system health, automates administration, troubleshoots complex issues, supports incident response and disaster recovery, ensures compliance, documents configurations, and mentors junior engineers.

Lead qualitative and quantitative project risk management across large CAPEX energy, mining, renewables, and infrastructure projects. Facilitate risk workshops, maintain risk registers, perform cost and schedule risk analyses (CSRA), integrate outputs into project controls and estimates, prepare risk reports, and improve risk tools and data libraries.

Lead design and delivery of self-service platform capabilities: provisioning, deployment, observability, and multi-region networking. Drive RFCs and cross-team alignment, build APIs (primarily in Go), implement Terraform/GitOps flows, improve EKS reliability and Grafana-based SLOs, and reduce operational toil via safe, auditable automation. Own on-call rotation and platform adoption outcomes.

The Infrastructure Engineer will ensure the reliability, security, and performance of Thatch's healthcare platform infrastructure. Responsibilities include designing infrastructure, improving CI/CD tools, and managing security and reliability across the stack.

As a Software Engineer for Data Infrastructure at Speechify, you'll manage data collection for model training, extend cloud infrastructure, and collaborate with scientists to enhance data quality and efficiency for AI models.

The Software Engineer will be responsible for data collection to support model training, operate cloud infrastructure, and enhance data ingestion pipelines.

Develop and manage data collection infrastructure for AI model training, utilizing cloud services and collaborating with scientists to enhance data quality and processing.

As a Software Engineer on the Data side of the AI team at Speechify, you'll manage data ingestion pipelines, extend cloud infrastructure, and collaborate with scientists to enhance data collection for model training, aiming to drive costs down while increasing throughput and quality.

The Software Engineer will manage data collection for AI model training by building datasets at scale, optimizing infrastructure, and collaborating with data scientists.

This role involves managing data acquisition and infrastructure for model training at Speechify, focusing on cloud operations and collaboration with AI scientists.

Responsible for data collection to support model training operations, operating the cloud infrastructure, and collaborating with AI team for data roadmaps.

The Software Engineer will develop data ingestion pipelines, manage cloud infrastructure for data collection, and collaborate with the AI team to enhance data quality and scale for model training.

The Software Engineer will build and operate the cloud infrastructure for data ingestion, collaborating with scientists to improve dataset quality, scale, and cost efficiency for AI model training.

The Software Engineer will handle data collection for model training, operate cloud infrastructure, and collaborate with AI scientists to improve data processing.

The Software Engineer will handle data collection for model training, operate cloud infrastructure, and collaborate on dataset roadmaps.

The Software Engineer will manage data acquisition and ingestion for AI model training, optimize cloud infrastructure, and collaborate on data strategy with the AI team.