Top Remote Infrastructure Engineer Jobs

Lead company-wide transformation of test automation and quality engineering: define vision and roadmap, architect scalable testing frameworks across server/web/mobile/desktop, integrate AI/LLM for test generation and flakiness management, establish observability and quality gates, mentor engineers, and partner with leadership to embed quality across the SDLC.

Build and maintain privacy-focused telecommunications infrastructure and deployment tooling. Own full lifecycle development, monitoring/instrumentation, high-availability systems, FedRAMP accreditation, and integration of telecom components. Shape engineering practices and balance short-term needs with long-term roadmap.

Build and scale the platform infrastructure to support mortgage origination: design cloud architecture, deploy and operate Kubernetes-based systems, manage databases, implement observability and incident response, and create internal developer tooling to improve reliability and engineering velocity.

Design and deliver complex physical and cloud data center infrastructures (network, compute, storage, telephony, middleware, database). Lead capacity planning, lifecycle management, standards, and vendor partnerships. Provide expert support during incidents, produce engineering documentation, and mentor junior engineers.

Lead design and engineering of complex physical and cloud data center network and telephony infrastructure. Drive requirements analysis, capacity planning, standards, vendor collaboration, project leadership, operational readiness, incident resolution, and mentorship to ensure scalable, performant network solutions.

Design, automate, deploy, and secure AWS and hybrid infrastructure using Terraform and CI/CD tooling. Build reusable IaC modules, maintain DevOps pipelines, implement logging/monitoring, and ensure compliance with zero-trust and frameworks (NIST/CIS/ISO). Collaborate across engineering, security, networking, and data teams to support mission continuity, DR, and documentation for federal environments.

Lead evolution of an internal developer platform into an AI-first, self-service system. Architect, build, and operate secure multi-tenant AWS EKS/Kubernetes infrastructure, developer tooling (CLIs, SDKs, portals), IaC/GitOps workflows, observability, and AI-assisted automation for provisioning, incident triage, and remediation while collaborating with application, SRE, and security teams.

Lead the Core Infrastructure team, focusing on Kubernetes platform ownership, multi-region expansion, AI infrastructure development, and enhancing security and performance.

Design, develop, and maintain high-performance distributed storage software and protocols (file, block, object). Integrate with hardware (NVMe, DPUs, GPU-direct), optimize performance and scalability, troubleshoot production data centers, collaborate with networking, compute, control plane and observability teams, and lead/mentor engineering teams.

Perform process design and rigorous review for gas, steam, and reciprocating power systems; validate PFDs/P&IDs, heat and mass balances, and datasheets; support system integration (fuel, cooling, exhaust, emissions), analyze plant performance and heat rate, drive FEED through commissioning, set scopes/schedules, and contribute to HAZOP/LOPA safety studies. Travel up to 20%.

Design, deploy, and maintain Azure Virtual Desktop (AVD) VDI solutions. Automate AVD tasks with scripts and workbooks, manage images and autoscaling, enforce security/compliance (STIGs, NIST, FISMA, FedRAMP), monitor costs and performance, troubleshoot Azure/AVD issues, and document environments.

Operate, monitor, and maintain Astronomer's managed Airflow platform and underlying cloud/Kubernetes infrastructure. Troubleshoot customer environments, participate in on-call rotation, build monitoring/automation, improve observability, and work directly with customers to meet SLAs and drive reliability.

Design, build, and operate large-scale on-prem Kubernetes platforms for AI/ML workloads. Own control plane and etcd, develop controllers/operators in Go, enable GPU workloads, implement IaC and AIOps, optimize performance, and provide on-call incident response while collaborating with ML teams.

Design, build, and operate large-scale on-prem Kubernetes platforms (OpenShift/Anthos) for AI/ML and GPU workloads. Own control plane and etcd lifecycle, build controllers/operators in Go, automate via IaC, improve observability and resource utilization, enable ML training/inference/LLM deployments, participate in on-call incident response, and mentor engineers.

Design, build, and operate large-scale on-prem Kubernetes (OpenShift/Anthos) platforms for AI/ML, managing control plane and cluster lifecycle, enabling GPU workloads, building controllers/operators in Go/Python, implementing IaC and AIOps automation, and supporting on-call incident response.

Design, build, and operate large-scale on-prem Kubernetes platforms (OpenShift/Anthos) for AI/ML workloads. Own control plane and etcd lifecycle, build operators and controllers in Go, enable GPU training/inference, implement IaC and automation, improve observability and platform reliability, participate in on-call incident response, and mentor engineers.

Lead architecture and rewrites for a scalable, resilient AI-first platform. Own backend systems, data storage performance, deployment pipelines, cloud infrastructure via IaC, observability, incident response, and analytics. Mentor engineers and enable rapid customer onboarding and AI-driven automation.

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.

As a Software Engineer in Data Infrastructure, you'll enhance audio data ingestion pipelines, operate cloud infrastructure, and collaborate with scientists on data strategies to support AI model training.

The role involves data collection for model training, integrating infrastructure and engineering to build datasets at large scales, collaborating with scientists to improve data quality and cost efficiency, and crafting a dataset roadmap.

The Software Engineer will manage data collection for model training, enhance cloud infrastructure, and collaborate with AI Scientists to improve data sourcing and processing efficiency.

The Software Engineer role focuses on data collection for model training, enhancing data ingestion pipelines, and collaborating with AI Scientists to improve data quality and efficiency.

Join Speechify as a Software Engineer responsible for data collection and management to support AI model training and enhance product offerings.

The role involves data collection and infrastructure management for model training at Speechify, focusing on data ingestion pipelines and collaboration with AI scientists to optimize datasets.

As a Software Engineer on the Data team, you will manage data collection for model training, extend cloud infrastructure, and collaborate with scientists to enhance data quality and efficiency.