Top Remote Infrastructure Engineer Jobs

Design and evolve systems for Motion's infrastructure, focusing on reliable and secure operations across APIs, Linux systems, and cloud environments with a focus on hands-on coding and engineering judgment.

You will architect and build cloud infrastructure, optimize systems, evolve CI/CD pipelines, manage infrastructure, and mentor engineers, focusing on AI-driven solutions.

Senior software developer responsible for implementing application-layer currency and supportability updates for middleware and microservices — including JDK/runtime upgrades, dependency remediation, certificate and credential updates, OpenShift/Linux compatibility, CI/CD and developer validation, rollback planning, and technical documentation.

Execute hardware bring-up, validation, and telemetry monitoring for Cerebras AI clusters in data centers. Perform power-on sequencing, first-line troubleshooting, log collection, incident support under senior guidance, and contribute feedback to tooling and documentation while learning system architecture and networking fundamentals.

Design and implement scalable backend systems for Patreon's platform. Collaborate with engineers and product managers to maintain and optimize performance.

The role involves designing and maintaining a scalable cloud infrastructure, working with cloud technologies, and improving system performance and security.

The role involves designing and scaling ML infrastructure for LLMs, including building training pipelines and deploying models in cloud and on-prem environments. Collaboration with engineers and managing GPU/TPU workloads is key.

The Site Reliability Engineer will develop, deploy, and operate AI infrastructure, focusing on high-performance and scalable machine learning systems using Kubernetes and cloud platforms.

Lead a team building large-scale ML model evaluation and orchestration frameworks for autonomous vehicles. Own data analysis workflows, dataset creation, statistical model evaluation, regression reporting, and tool development (AWS Kubernetes orchestration, ReSimulation). Provide technical leadership, mentorship, and manage project timelines and deliverables.

Design, build, and maintain cloud-based data pipelines and infrastructure on AWS, integrating on-prem and cloud flows. Implement IaC, CI/CD, containerization, observability, and automation to ensure high-throughput, reliable data ingestion and processing for autonomous systems.

Design, develop, and optimize system software and firmware for SoC-based O-RAN infrastructure. Implement power-management policies (DVFS, clock/power gating, thermal control), analyze RU/DU workloads, build performance and power models, create measurement and test tooling, validate on simulation/emulation and silicon, and influence SoC and platform architectures for 5G/6G deployments.

Design, maintain, and optimize cloud infrastructure and CI/CD systems. Solve complex DevOps problems, support engineering teams, develop cloud migration strategies, and build tools to enable scalable, secure deployments.

Architect and build TeraWave Point of Presence infrastructure, implement and optimize wire-speed dataplane using DPDK/VPP, tune IP networking stacks (BGP/OSPF), drive performance engineering at the software-hardware interface, mentor engineers, and integrate PoP systems with the broader satellite communications ecosystem.

Build and operate CrewAI's infrastructure across AWS, Azure, and GCP. Own containerized deployments, CI/CD pipelines, observability, secrets, networking, databases, and on-call reliability. Harden security, automate deployments and installs, partner with runtime and product engineers, and reduce operational toil through tooling and automation.

The Senior Backend Engineer will develop, test, and maintain scalable integrations, support cross-functional teams, and enhance developer experiences.

Develop and maintain production Python services for high-scale rendering, caching, and delivery. Design systems focused on reliability, cost, and performance. Build infrastructure-as-code and automation (Terraform, CI/CD, Docker). Own deployment, monitoring, incident response, and on-call duties. Collaborate on cloud cost optimization and produce operational documentation.

Build and optimize backend services and platform infrastructure for trading on the Aptos blockchain. Develop scalable APIs, indexing services, data pipelines, and node infrastructure. Write production-ready, well-tested code, collaborate with protocol, infrastructure, and product teams, and help shape technical direction. Mentor and may lead other engineers as the team scales.

Design and maintain Terraform and OCI Resource Manager IaC for standardized tenant onboarding. Automate landing zones, identity, network baselines, governance, and security guardrails. Build CI/CD pipelines, reusable templates (DNS, VCN, Cloud Guard, logging, IAM policies, tagging), enforce policy-as-code, and accelerate tenant provisioning.

Build and automate internal tools and services to operate Qdrant Cloud at scale. Develop platform components in Go and Python, improve Kubernetes automation, provisioning, reliability, scalability, and observability. Collaborate on architecture, participate in incident response, and reduce manual operational toil through automation.

Design, build, and optimize production-grade Rust systems for low-latency model serving and real-time data ingestion. Implement high-throughput backend APIs, caching, and memory-efficient components. Debug distributed systems, establish benchmarking and monitoring, and collaborate with Applied Scientists to translate ML advances into scalable runtime systems.

Operate and optimize large-scale LLM pre-training on 1,000+ GPU clusters using PyTorch, DeepSpeed, or Megatron-LM. Improve networking (InfiniBand/RDMA), memory management, checkpointing, and failure recovery. Manage SLURM/Kubernetes GPU clusters and apply systems engineering (C++, CUDA, Python) and 3D parallelism techniques.

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.

Design, orchestrate, and optimize large-scale LLM pre-training across 1,000+ GPUs. Implement 3D parallelism, manage GPU clusters (SLURM/Kubernetes), optimize InfiniBand/RDMA networking and memory, and automate checkpointing and failure recovery for long training runs.

Design, build, and operate secure, highly available cloud environments using IaC, CI/CD, and DevSecOps. Implement networking, IAM, compute, storage, serverless, containers, observability, FinOps, and SRE practices; produce design docs and automation pipelines to migrate and optimize workloads on AWS/Azure/GCP.